From 2fbc2b3a11c40a7dbb6a9d775009244999631ec0 Mon Sep 17 00:00:00 2001 From: acp29 Date: Mon, 10 Jun 2024 23:48:20 +0100 Subject: [PATCH] `bootlm`: added relative likelihoods of models to PRED_ERR --- DESCRIPTION | 4 ++-- inst/bootlm.m | 8 ++++++-- matlab/statistics-resampling.mltbx | Bin 348009 -> 348102 bytes matlab/statistics-resampling.prj | 4 ++-- 4 files changed, 10 insertions(+), 6 deletions(-) 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 a7d342da8240c912115b7c3d7a050e9efc27c033..b7e989607bfe727774da6cbbc69527fe85464cb7 100644 GIT binary patch delta 28901 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zm1N%mARzwni1xR*7)fx=94-XJ2c!Qj{u!(!1tcN0kL5Ize?8N=>IC2 z=&eK-0wEx15g{ND{?!mH@VFH4Z4Lk*zY2goDln`x@NI$u(@MVr=geS9X&~|2;amO% zo<4$urGX#bfYMjs9R_$n8c6c?`|z*Ar7aj*=05CZ zXC}tK`~O?tU#4mQtp$o#rglgO2!ekx{lEl*g|UEyU_JTQe)&6m*~q_Ij{*k>&cXrW z(f=>gkC4@tuvdnu*ZAL-|I?-!9Pp$(kox}&c<&T|n2-s$Krk}iYj6FnfcS4?{&hkA zt1&EKLj@o?>0c$Rr-RtR*G$P*^8fb!KlLo&1HsA!K%zIoH{DW^Yo_E^-Rajz`7gp{ zf;U|}upJ=~k>P)j1;?^7i<$xgf{Ydd;`Mz0KU)JK5X?*jB&Pe{BH6g2s9# - + 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