1 | |
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2 | ----- Documentation for Stat\cov2cor.pro ----- |
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3 | NAME: |
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4 | COV2COR |
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5 | |
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6 | PURPOSE: |
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7 | CONVERT COVARIANCE MATRIX TO MATRIX OF CORRELATION COEFFICIENTS |
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8 | |
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9 | CATEGORY: |
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10 | statistics |
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11 | |
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12 | CALLING SEQUENCE: |
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13 | COV2COR, COV, SIGMA, COR |
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14 | |
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15 | INPUTS: |
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16 | COV = COVARIANCE MATRIX |
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17 | |
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18 | OUTPUTS: |
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19 | SIGMA = ERROR ARRAY |
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20 | COR = CORRELATION MATRIX |
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21 | |
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22 | COMMON BLOCKS: |
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23 | NONE |
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24 | |
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25 | SIDE EFFECTS: |
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26 | NONE |
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27 | |
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28 | REQUIREMENTS: |
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29 | COR MUST BE SQUARE, SYMMETRIC, WITH POSITIVE DIAGONALS |
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30 | |
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31 | PROCEDURE: |
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32 | COV = COR / (SIGMA # SIGMA) |
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33 | WITH: SIGMA = SQRT(DIAG(COV)) |
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34 | |
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35 | LOCAL PROCEDURE CALLED: |
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36 | NONE |
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37 | |
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38 | LOCAL FUNCTION USED: |
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39 | NONE |
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40 | |
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41 | LOCAL SYSTEM VARIABLE USED: |
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42 | NONE |
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43 | |
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44 | REVISION HISTORY: |
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45 | Written by pcr 2010/02/01 |
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46 | from www.boulder.swri.edu/~layoung/idl/layoung_v5/math/cov2cor.pro |
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47 | |
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48 | ----- Documentation for Stat\get_outlier_fences.pro ----- |
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49 | NAME: |
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50 | GET_OUTLIER_FENCES |
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51 | |
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52 | AUTHOR: |
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53 | pierre.cruzalebes@oca.eu |
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54 | |
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55 | PURPOSE: |
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56 | return lower and upper fences identifying extreme values in tails |
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57 | of univariate distribution (outliers). |
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58 | Estimation of percentiles following NIST-recommended method |
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59 | http://www.itl.nist.gov/div898/handbook/prc/section2/prc252.htm |
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60 | For small nber of data, estimate percentiles using normal CDF |
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61 | |
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62 | CATEGORY: |
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63 | statistics |
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64 | |
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65 | CALLING SEQUENCE: |
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66 | FENCES=GET_OUTLIER_FENCES(X,ALFA,COEFF) |
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67 | |
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68 | INPUTS: |
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69 | X = experimental data distribution. |
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70 | ALFA = percentage of experimental data included in the interpercentile range. |
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71 | (must be gt 0 and lt 1, e.g. =0.5 for quartile-based outliers). |
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72 | COEFF = outlier coefficient defining types of outliers |
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73 | (=1.5 for mild outliers, =3 for extreme outliers). |
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74 | |
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75 | OUTPUTS: |
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76 | Function result = FENCES = 2-element array of outlier fences |
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77 | (FENCES(0)=lower fence, FENCES(1)=upper fence). |
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78 | |
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79 | OPTIONAL OUTPUT PARAMETERS: |
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80 | NONE. |
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81 | |
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82 | COMMON BLOCKS: |
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83 | NONE. |
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84 | |
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85 | SIDE EFFECTS: |
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86 | NONE. |
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87 | |
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88 | RESTRICTIONS: |
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89 | NONE. |
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90 | |
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91 | PROCEDURE: |
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92 | |
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93 | LOCAL PROCEDURE CALLED: |
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94 | NONE. |
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95 | |
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96 | LOCAL FUNCTION USED: |
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97 | NONE. |
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98 | |
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99 | LOCAL SYSTEM VARIABLE USED: |
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100 | NB_DATA_BOOT |
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101 | |
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102 | REVISION HISTORY: |
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103 | Written by pcr 2009/02/02 |
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104 | Last modification by pcr 2010/12/12 |
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105 | |
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106 | ----- Documentation for Stat\loca_scale_chi2.pro ----- |
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107 | NAME: |
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108 | LOCA_SCALE_CHI2 |
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109 | |
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110 | AUTHOR: |
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111 | pierre.cruzalebes@oca.eu |
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112 | |
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113 | PURPOSE: |
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114 | return location and scale parameters of standard chi-square distribution |
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115 | for experimental data, using median (for location) and interpercentile range (for scale). |
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116 | interquartile range (ALFA=0.75) usually used as robust measure of scale |
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117 | Estimation of percentiles following NIST-recommended method |
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118 | http://www.itl.nist.gov/div898/handbook/prc/section2/prc252.htm |
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119 | |
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120 | CATEGORY: |
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121 | statistics |
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122 | |
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123 | CALLING SEQUENCE: |
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124 | LOCA_SCALE_CHI2,X,ALFA,NU,LOC,SCA |
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125 | |
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126 | INPUTS: |
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127 | X = experimental data set. |
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128 | ALFA = percentage of experimental data included in the interpercentile range (must be gt 0 and lt 1). |
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129 | NU = number of degrees of freedom. |
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130 | |
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131 | OUTPUTS: |
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132 | LOC = location parameter of standard chi-square distribution. |
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133 | SCA = scale parameter of standard chi-square distribution. |
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134 | |
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135 | OPTIONAL OUTPUT PARAMETERS: |
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136 | NONE. |
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137 | |
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138 | COMMON BLOCKS: |
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139 | NONE. |
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140 | |
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141 | SIDE EFFECTS: |
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142 | NONE. |
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143 | |
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144 | RESTRICTIONS: |
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145 | NONE. |
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146 | |
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147 | PROCEDURE: |
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148 | |
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149 | LOCAL PROCEDURE CALLED: |
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150 | NONE |
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151 | |
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152 | LOCAL FUNCTION USED: |
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153 | NONE |
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154 | |
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155 | LOCAL SYSTEM VARIABLE USED: |
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156 | NONE |
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157 | |
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158 | REVISION HISTORY: |
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159 | Written by pcr 2008/01/24 |
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160 | last modification by pcr 2009/09/31 |
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161 | |
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162 | ----- Documentation for Stat\loca_scale_norm.pro ----- |
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163 | NAME: |
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164 | LOCA_SCALE_NORM |
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165 | |
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166 | AUTHOR: |
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167 | pierre.cruzalebes@oca.eu |
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168 | |
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169 | PURPOSE: |
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170 | return location and scale parameters of standard normal distribution |
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171 | for experimental data, using median (for location) and interpercentile |
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172 | range (for scale). |
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173 | Estimation of percentiles following NIST-recommended method |
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174 | http://www.itl.nist.gov/div898/handbook/prc/section2/prc252.htm |
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175 | |
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176 | CATEGORY: |
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177 | statistics |
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178 | |
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179 | CALLING SEQUENCE: |
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180 | LOCA_SCALE_NORM,X,ALFA,LOC,SCA |
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181 | |
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182 | INPUTS: |
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183 | X = experimental data set. |
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184 | ALFA = percentage of experimental data included in the interpercentile |
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185 | range (must be gt 0 and lt 1). |
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186 | |
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187 | OUTPUT: |
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188 | LOC = location parameter of standard normal distribution. |
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189 | SCA = scale parameter of standard normal distribution. |
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190 | |
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191 | OPTIONAL OUTPUT PARAMETERS: |
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192 | NONE. |
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193 | |
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194 | COMMON BLOCKS: |
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195 | NONE. |
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196 | |
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197 | SIDE EFFECTS: |
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198 | NONE. |
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199 | |
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200 | RESTRICTIONS: |
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201 | NONE. |
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202 | |
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203 | PROCEDURE: |
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204 | |
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205 | LOCAL PROCEDURE CALLED: |
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206 | NONE |
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207 | |
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208 | LOCAL FUNCTION USED: |
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209 | NONE |
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210 | |
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211 | LOCAL SYSTEM VARIABLE USED: |
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212 | NONE |
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213 | |
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214 | REVISION HISTORY: |
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215 | Written by pcr 2008/05/31 |
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216 | last modification by pcr 2009/04/14 |
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217 | |
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218 | ----- Documentation for Stat\mem_stdev.pro ----- |
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219 | NAME: |
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220 | MEM_STDEV |
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221 | |
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222 | AUTHOR: |
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223 | pierre.cruzalebes@oca.eu |
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224 | |
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225 | PURPOSE: |
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226 | compute standard deviation of asymmetric distribution from maximum entropy principle. |
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227 | |
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228 | CATEGORY: |
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229 | statistics |
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230 | |
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231 | CALLING SEQUENCE: |
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232 | MEMSTD = MEM_STDEV(LOWER_ERROR,UPPER_ERROR) |
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233 | |
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234 | INPUTS: |
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235 | LOWER_ERROR = lower error. |
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236 | UPPER_ERROR = upper error. |
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237 | |
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238 | OPTIONAL INPUT PARAMETER: |
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239 | none. |
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240 | |
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241 | OUTPUTS: |
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242 | Function result = MEMSTD = standard deviation of distribution. |
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243 | |
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244 | OPTIONAL OUTPUT PARAMETER: |
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245 | NONE. |
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246 | |
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247 | COMMON BLOCKS: |
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248 | NONE. |
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249 | |
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250 | SIDE EFFECTS: |
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251 | NONE. |
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252 | |
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253 | RESTRICTIONS: |
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254 | NONE. |
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255 | |
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256 | PROCEDURE: |
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257 | memvar=MEMSTD^2=UPPER_ERROR*LOWER_ERROR-(UPPER_ERROR-LOWER_ERROR)/lambda |
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258 | where lambda is computed according to JCGM 100:2008, section 4.3.8, note 2 |
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259 | |
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260 | LOCAL PROCEDURE CALLED: |
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261 | NONE |
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262 | |
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263 | LOCAL FUNCTION USED: |
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264 | NONE |
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265 | |
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266 | LOCAL SYSTEM VARIABLE USED: |
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267 | NONE |
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268 | |
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269 | REVISION HISTORY: |
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270 | Written by pcr 2009/10/05 |
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271 | Last modification by pcr 2010/12/07 |
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272 | |
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273 | ----- Documentation for Stat\plot_distri.pro ----- |
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274 | NAME: |
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275 | PLOT_DISTRI |
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276 | |
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277 | AUTHOR: |
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278 | pierre.cruzalebes@oca.eu |
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279 | |
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280 | PURPOSE: |
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281 | plot chi-square and parameter statistics, used with fit_model and fit_sed |
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282 | |
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283 | CATEGORY: |
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284 | statistics |
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285 | |
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286 | CALLING SEQUENCE: |
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287 | PLOT_DISTRI,DELTACHI2,NU,PARA,FTIT,OUTPUT_FILE_STEM,WSKIP,CLEVEL |
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288 | |
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289 | INPUTS: |
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290 | DELTACHI2 = row vector of reduced chi-square differences. |
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291 | NU = number of degrees of freedom. |
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292 | FTIT = row vector of string chains for plot of free parameter axis titles. |
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293 | PARA = 2-dim array of free model parameters, sorted in ascending order |
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294 | of chi-square diff, length=length(DELTACHI2)*length(FTIT). |
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295 | OUTPUT_FILE_STEM = output file stem for writing in postscript files. |
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296 | WSKIP = index of first newly created window in current procedure. |
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297 | CLEVEL = confidence level. |
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298 | |
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299 | OUTPUT: |
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300 | WSKIP = index of next newly created window after current procedure. |
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301 | |
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302 | OPTIONAL OUTPUT PARAMETERS: |
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303 | NONE. |
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304 | |
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305 | COMMON BLOCKS: |
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306 | NONE. |
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307 | |
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308 | SIDE EFFECTS: |
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309 | NONE. |
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310 | |
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311 | RESTRICTIONS: |
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312 | NONE. |
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313 | |
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314 | PROCEDURE: |
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315 | uniform order statistic medians (quantiles) given by |
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316 | http://www.itl.nist.gov/div898/handbook/eda/section3/probplot.htm |
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317 | standardization of mean-squares from |
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318 | Wilson & Hilferty, Proc. of Nat. Acad. of Sciences of USA, 17, 684-688 (1931) |
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319 | |
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320 | LOCAL PROCEDURE CALLED: |
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321 | LOCA_SCALE_CHI2 |
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322 | RESET_PLOT |
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323 | |
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324 | LOCAL FUNCTION USED: |
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325 | NONE |
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326 | |
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327 | LOCAL SYSTEM VARIABLE USED: |
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328 | OBS_PATH |
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329 | PLOT_DEV |
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330 | |
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331 | REVISION HISTORY: |
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332 | Written by pcr 2008/04/08 |
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333 | last modification by pcr 2011/01/14 |
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334 | |
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335 | ----- Documentation for Stat\rect_stdev.pro ----- |
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336 | NAME: |
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337 | RECT_STDEV |
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338 | |
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339 | AUTHOR: |
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340 | pierre.cruzalebes@oca.eu |
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341 | |
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342 | PURPOSE: |
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343 | compute standard deviation of rectangular (uniform) distribution. |
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344 | |
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345 | CATEGORY: |
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346 | statistics |
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347 | |
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348 | CALLING SEQUENCE: |
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349 | RECSTD = RECT_STDEV(LOWER_ERROR,UPPER_ERROR,CONFID_LEVEL,LOWER_BOUND,UPPER_BOUND) |
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350 | |
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351 | INPUTS: |
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352 | LOWER_ERROR = lower error. |
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353 | UPPER_ERROR = upper error. |
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354 | CONFID_LEVEL = level of confidence. |
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355 | |
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356 | OPTIONAL INPUT PARAMETER: |
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357 | none. |
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358 | |
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359 | OUTPUTS: |
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360 | Function result = RECSTD = standard deviation of distribution. |
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361 | |
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362 | OPTIONAL OUTPUT PARAMETER: |
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363 | NONE. |
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364 | |
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365 | COMMON BLOCKS: |
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366 | NONE. |
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367 | |
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368 | SIDE EFFECTS: |
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369 | NONE. |
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370 | |
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371 | RESTRICTIONS: |
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372 | NONE. |
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373 | |
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374 | PROCEDURE: |
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375 | recvar=RECSTD^2=cover^2*(UPPER_ERROR+LOWER_ERROR)^2/12 |
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376 | where cover=sqrt(2)/3*inv_erf(CONFID_LEVEL) |
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377 | |
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378 | LOCAL PROCEDURE CALLED: |
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379 | NONE |
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380 | |
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381 | LOCAL FUNCTION USED: |
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382 | NONE |
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383 | |
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384 | LOCAL SYSTEM VARIABLE USED: |
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385 | NONE |
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386 | |
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387 | REVISION HISTORY: |
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388 | Written by pcr 2009/10/15 |
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389 | |
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390 | ----- Documentation for Stat\tri_stdev.pro ----- |
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391 | NAME: |
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392 | TRI_STDEV |
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393 | |
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394 | AUTHOR: |
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395 | pierre.cruzalebes@oca.eu |
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396 | |
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397 | PURPOSE: |
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398 | compute standard deviation and upper/lower bounds of triangular |
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399 | distribution from quantiles. |
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400 | |
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401 | CATEGORY: |
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402 | statistics |
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403 | |
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404 | CALLING SEQUENCE: |
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405 | TRISTD = TRI_STDEV(MODE_VAL,LOWER_QUANT,UPPER_QUANT,LOWER_PROB, |
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406 | UPPER_PROB,UPPER_BOUND,LOWER_BOUND) |
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407 | |
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408 | INPUTS: |
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409 | MODE_VAL = mode value. |
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410 | LOWER_QUANT = lower quantile. |
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411 | UPPER_QUANT = upper quantile. |
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412 | LOWER_PROB = probability of lower quantile. |
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413 | UPPER_QUANT = probability of upper quantile. |
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414 | |
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415 | OPTIONAL INPUT PARAMETER: |
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416 | none. |
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417 | |
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418 | OUTPUTS: |
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419 | Function result = TRISTD = standard deviation of |
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420 | triangular distribution. |
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421 | UPPER_BOUND = upper limit of triangular distribution |
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422 | LOWER_BOUND = lower limit |
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423 | |
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424 | OPTIONAL OUTPUT PARAMETER: |
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425 | NONE. |
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426 | |
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427 | COMMON BLOCKS: |
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428 | NONE. |
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429 | |
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430 | SIDE EFFECTS: |
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431 | NONE. |
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432 | |
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433 | RESTRICTIONS: |
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434 | NONE. |
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435 | |
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436 | PROCEDURE: |
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437 | trivar=TRISTD^2=(LOWER_BOUND^2+MODE_VAL^2+UPPER_BOUND^2 |
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438 | -LOWER_BOUND*MODE_VAL-UPPER_BOUND*MODE_VAL |
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439 | -LOWER_BOUND*UPPER_BOUND)/18 |
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440 | where LOWER_BOUND and UPPER_BOUND are triangular distribution |
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441 | limits calculated from upper and lower quantiles |
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442 | according to Kotz & Van Dorp (2004) section 1.6 |
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443 | |
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444 | LOCAL PROCEDURE CALLED: |
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445 | NONE |
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446 | |
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447 | LOCAL FUNCTION USED: |
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448 | NONE |
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449 | |
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450 | LOCAL SYSTEM VARIABLE USED: |
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451 | EPSILON |
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452 | |
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453 | REVISION HISTORY: |
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454 | Written by pcr 2009/10/05 |
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455 | last modification by pcr 2010/12/07 |
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456 | |
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457 | ----- Documentation for Stat\wavg.pro ----- |
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458 | NAME: |
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459 | WAVG |
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460 | |
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461 | AUTHOR: |
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462 | pierre.cruzalebes@oca.eu |
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463 | |
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464 | PURPOSE: |
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465 | compute weighted mean of data vector. |
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466 | |
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467 | CATEGORY: |
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468 | statistics |
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469 | |
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470 | CALLING SEQUENCE: |
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471 | WMEAN = WAVG(WEIGHT,DATA) |
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472 | |
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473 | INPUTS: |
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474 | WEIGHT = row vector of weights . |
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475 | DATA = row vector of data (same length as WEIGHT). |
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476 | |
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477 | OUTPUTS: |
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478 | Function result = WMEAN = weighted mean. |
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479 | |
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480 | OPTIONAL OUTPUT PARAMETER: |
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481 | NONE. |
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482 | |
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483 | COMMON BLOCKS: |
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484 | NONE. |
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485 | |
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486 | SIDE EFFECTS: |
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487 | NONE. |
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488 | |
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489 | RESTRICTIONS: |
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490 | NONE. |
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491 | |
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492 | PROCEDURE: |
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493 | |
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494 | LOCAL PROCEDURE CALLED: |
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495 | NONE |
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496 | |
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497 | LOCAL FUNCTION USED: |
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498 | NONE |
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499 | |
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500 | LOCAL SYSTEM VARIABLE USED: |
---|
501 | NONE |
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502 | |
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503 | REVISION HISTORY: |
---|
504 | Written by pcr 2008/05/27 |
---|
505 | last modification by pcr 2010/11/10 |
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506 | |
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507 | ----- Documentation for Stat\wstdev.pro ----- |
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508 | NAME: |
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509 | WSTDEV |
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510 | |
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511 | AUTHOR: |
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512 | pierre.cruzalebes@oca.eu |
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513 | |
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514 | PURPOSE: |
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515 | compute weighted mean of data vector |
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516 | and weighted standard deviation (or mean standard weighted error). |
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517 | |
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518 | CATEGORY: |
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519 | statistics |
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520 | |
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521 | CALLING SEQUENCE: |
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522 | WSTD = WSTDEV(WEIGHT,DATA,WMEAN,ERROR) |
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523 | |
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524 | INPUTS: |
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525 | WEIGHT = row vector of weights . |
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526 | DATA = row vector of data (same length as WEIGHT). |
---|
527 | |
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528 | OPTIONAL INPUT PARAMETER: |
---|
529 | ERROR = row vector of errors (same length as WEIGHT). |
---|
530 | |
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531 | OUTPUTS: |
---|
532 | Function result = WSTD = unbiased estimator of weighted standard deviation (or mean weighted error). |
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533 | WMEAN = weighted mean. |
---|
534 | |
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535 | OPTIONAL OUTPUT PARAMETER: |
---|
536 | NONE. |
---|
537 | |
---|
538 | COMMON BLOCKS: |
---|
539 | NONE. |
---|
540 | |
---|
541 | SIDE EFFECTS: |
---|
542 | NONE. |
---|
543 | |
---|
544 | RESTRICTIONS: |
---|
545 | NONE. |
---|
546 | |
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547 | PROCEDURE: |
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548 | WMEAN=SUM(WEIGHT*DATA)/SUM(WEIGHT) |
---|
549 | following http://pygsl.sourceforge.net/reference/pygsl/node52.html |
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550 | and http://www.gnu.org/software/gsl/manual/html_node/Weighted-Samples.html : |
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551 | WSTDEV^2=SUM(WEIGHT)/((SUM(WEIGHT))^2-SUM(WEIGHT^2)) |
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552 | *SUM(WEIGHT*(DATA-WMEAN)^2) |
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553 | if ERROR vector provided : |
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554 | WSTDEV^2=SUM(WEIGHT^2*ERROR^2)/(SUM(WEIGHT))^2 |
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555 | |
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556 | LOCAL PROCEDURE CALLED: |
---|
557 | NONE |
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558 | |
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559 | LOCAL FUNCTION USED: |
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560 | NONE |
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561 | |
---|
562 | LOCAL SYSTEM VARIABLE USED: |
---|
563 | NONE |
---|
564 | |
---|
565 | REVISION HISTORY: |
---|
566 | Written by pcr 2008/05/27 |
---|
567 | last modification by pcr 2010/11/13 |
---|
568 | |
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569 | ----- Documentation for Stat\wsterr.pro ----- |
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570 | NAME: |
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571 | WSTERR |
---|
572 | |
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573 | AUTHOR: |
---|
574 | pierre.cruzalebes@oca.eu |
---|
575 | |
---|
576 | PURPOSE: |
---|
577 | compute weighted mean of data vector |
---|
578 | and standard error on weighted mean |
---|
579 | |
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580 | CATEGORY: |
---|
581 | statistics |
---|
582 | |
---|
583 | CALLING SEQUENCE: |
---|
584 | WSTE = WSTERR(WEIGHT,DATA,WMEAN) |
---|
585 | |
---|
586 | INPUTS: |
---|
587 | WEIGHT = row vector of weights . |
---|
588 | DATA = row vector of data (same length as WEIGHT). |
---|
589 | |
---|
590 | OPTIONAL INPUT PARAMETER: |
---|
591 | NONE. |
---|
592 | |
---|
593 | OUTPUTS: |
---|
594 | Function result = WSTE = unbiased estimator of standard error |
---|
595 | on weighted mean. |
---|
596 | WMEAN = weighted mean. |
---|
597 | |
---|
598 | OPTIONAL OUTPUT PARAMETER: |
---|
599 | NONE. |
---|
600 | |
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601 | COMMON BLOCKS: |
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602 | NONE. |
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603 | |
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604 | SIDE EFFECTS: |
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605 | NONE. |
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606 | |
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607 | RESTRICTIONS: |
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608 | NONE. |
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609 | |
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610 | PROCEDURE: |
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611 | WMEAN=SUM(WEIGHT*DATA)/SUM(WEIGHT) |
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612 | following Gatz & Smith, Atmosph. Env. 29, 11, pp. 1185-1193 (1995) : |
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613 | WSTERR^2 = (N/N-1)/(SUM(WEIGHT))^2 |
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614 | * ( TOTAL((WEIGHT*DATA-AVG(WEIGHT)*WMEAN)^2) |
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615 | - 2.*WMEAN*TOTAL((WEIGHT-AVG(WEIGHT)) |
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616 | * (WEIGHT*DATA-AVG(WEIGHT)*WMEAN)) |
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617 | + WMEAN^2*TOTAL((WEIGHT-AVG(WEIGHT))^2) ) |
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618 | |
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619 | LOCAL PROCEDURE CALLED: |
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620 | NONE |
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621 | |
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622 | LOCAL FUNCTION USED: |
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623 | NONE |
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624 | |
---|
625 | LOCAL SYSTEM VARIABLE USED: |
---|
626 | NONE |
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627 | |
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628 | MODIFICATION HISTORY: |
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629 | Written by pcr 2010/11/13 |
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630 | |
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