diff --git a/DESCRIPTION b/DESCRIPTION index 2287c81..e82e19d 100755 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ name: statistics-resampling -version: 5.5.18 -date: 2024-06-04 +version: 5.5.19 +date: 2024-06-10 author: Andrew Penn maintainer: Andrew Penn title: A statistics package with a variety of resampling tools diff --git a/inst/bootlm.m b/inst/bootlm.m index cc9dca7..580a905 100755 --- a/inst/bootlm.m +++ b/inst/bootlm.m @@ -464,6 +464,7 @@ % - 'PE': Bootstrap estimate of prediction error % - 'PRESS': Bootstrap estimate of predicted residual error sum of squares % - 'RSQ_pred': Bootstrap estimate of predicted R-squared +% - 'RL': Relative likelihood compared to the intercept-only model % % The linear models evaluated are the same as for AOVSTAT, except that the % output also includes the statistics for the intercept-only model. Note @@ -478,7 +479,7 @@ % installed and loaded, then these computations will be automatically % accelerated by parallel processing on platforms with multiple processors % -% bootlm (version 2024.05.17) +% bootlm (version 2024.06.10) % Author: Andrew Charles Penn % https://www.researchgate.net/profile/Andrew_Penn/ % @@ -2131,9 +2132,12 @@ SST = RSS{1}; % Total sum of squares PE_RSQ = 1 - PRESS / SST; % Predicted R-squared calculated % by refined bootstrap + RL = exp (-0.5 * (PE - PE(1))); % Relative likelihood (compared + % to the intercept-only model) % Prepare output - PRED_ERR = struct ('MODEL', [], 'PE', PE, 'PRESS', PRESS, 'RSQ_pred', PE_RSQ); + PRED_ERR = struct ('MODEL', [], 'PE', PE, 'PRESS', PRESS, 'RSQ_pred', ... + PE_RSQ, 'RL', RL); end diff --git a/matlab/statistics-resampling.mltbx b/matlab/statistics-resampling.mltbx index a7d342d..b7e9896 100644 Binary files a/matlab/statistics-resampling.mltbx and b/matlab/statistics-resampling.mltbx differ diff --git a/matlab/statistics-resampling.prj b/matlab/statistics-resampling.prj index c85f29e..662119c 100644 --- a/matlab/statistics-resampling.prj +++ b/matlab/statistics-resampling.prj @@ -1,5 +1,5 @@ - + statistics-resampling Andrew Penn andy.c.penn@gmail.com @@ -7,7 +7,7 @@ Statistical analysis using resampling methods The statistics-resampling package is an Octave package and Matlab toolbox that can be used to perform a wide variety of statistics tasks using non-parametric resampling methods. In particular, the functions included can be used to estimate bias, uncertainty (standard errors and confidence intervals), prediction error, and calculate p-values for null hypothesis significance tests. Variations of the resampling methods are included that improve the accuracy of the statistics for small samples and samples with complex dependence structures. Y:\Documents\GitHub\statistics-resampling\doc\icon.png - 5.5.18 + 5.5.19 ${PROJECT_ROOT}\statistics-resampling.mltbx