Update matlab toolbox and manual

Author: acp29

docs/description.json

@@ -8,7 +8,7 @@
     "version": "5.5.18",
     "description": "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.",
     "shortdescription": "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",
-    "date": "2024-06-03",
+    "date": "2024-06-04",
     "title": "A statistics package with a variety of resampling tools",
     "author": "Andrew Penn <[email protected]>",
     "maintainer": "Andrew Penn <[email protected]>",

docs/function/boot1way.html

@@ -529,7 +529,7 @@ <h3><a name="7">Demonstration 7</a></h3>
 -----------------------------------------------------------------------------
 | Comparison |     Test # |      Ref # | Difference |          t |        p |
 |------------|------------|------------|------------|------------|----------|
-|          1 |          2 |          1 |    +0.4666 |      +0.82 |     .475 |
+|          1 |          2 |          1 |    -0.3210 |      -0.67 |     .479 |
 
 -----------------------------------------------------------------------------
 |    GROUP # |                                       GROUP label |        N |
@@ -574,7 +574,7 @@ <h3><a name="8">Demonstration 8</a></h3>
 -----------------------------------------------------------------------------
 | Comparison |     Test # |      Ref # | Difference |          t |        p |
 |------------|------------|------------|------------|------------|----------|
-|          1 |          2 |          1 |    -0.3427 |      -0.26 |     .657 |
+|          1 |          2 |          1 |    +0.7003 |      +0.63 |     .424 |
 
 -----------------------------------------------------------------------------
 |    GROUP # |                                       GROUP label |        N |

docs/function/bootbayes.html

@@ -191,7 +191,7 @@ <h3><a name="1">Demonstration 1</a></h3>
 
 Posterior Statistics: 
  original     bias         median       stdev       CI_lower      CI_upper
- +184.5       -0.006728    +184.5       1.339       +181.9        +187.3</pre>
+ +184.5       -0.02286     +184.5       1.240       +182.1        +186.9</pre>
 </div>
 
 <h3><a name="2">Demonstration 2</a></h3>
@@ -228,8 +228,8 @@ <h3><a name="2">Demonstration 2</a></h3>
 
 Posterior Statistics: 
  original     bias         median       stdev       CI_lower      CI_upper
- +175.5       -0.05967     +175.4       2.409       +170.9        +180.1    
- +0.1904      +0.0003230   +0.1934      0.07855     +0.04061      +0.3366</pre>
+ +175.5       -0.05767     +175.4       2.381       +171.3        +180.3    
+ +0.1904      +0.001144    +0.1941      0.07872     +0.03729      +0.3456</pre>
 </div>
 
 <p>Package: <a href="../index.html">statistics-resampling</a></p>

docs/function/bootci.html

@@ -468,8 +468,8 @@ <h3><a name="10">Demonstration 10</a></h3>
 <p>Produces the following output</p>
 <pre class="example">ci =
 
-    -0.065061     -0.18734
-      0.91342      0.76035</pre>
+     -0.43651     -0.55144
+      0.52378      0.24516</pre>
 </div>
 
 <h3><a name="11">Demonstration 11</a></h3>

docs/function/bootclust.html

@@ -376,8 +376,8 @@ <h3><a name="7">Demonstration 7</a></h3>
 
 Bootstrap Statistics: 
  original     bias         std_error    CI_lower     CI_upper  
- +0.06426     -0.01999     +0.2166      -0.3321      +0.3869    
- +0.001783    -0.01699     +0.1997      -0.2995      +0.3375</pre>
+ -0.03417     -0.001008    +0.2100      -0.3711      +0.3182    
+ +0.1006      +0.0007326   +0.1678      -0.1282      +0.4366</pre>
 </div>
 
 <h3><a name="8">Demonstration 8</a></h3>
@@ -406,8 +406,8 @@ <h3><a name="8">Demonstration 8</a></h3>
 
 Bootstrap Statistics: 
  original     bias         std_error    CI_lower     CI_upper  
- +0.4194      +0.02432     +0.3358      -0.3491      +0.8449    
- -0.07037     -0.06238     +0.3947      -0.7081      +0.5528</pre>
+ +0.4141      -0.02314     +0.1388      +0.1821      +0.6245    
+ +0.4913      -0.01465     +0.1777      +0.2410      +0.8309</pre>
 </div>
 
 <h3><a name="9">Demonstration 9</a></h3>

docs/function/bootknife.html

@@ -442,8 +442,8 @@ <h3><a name="8">Demonstration 8</a></h3>
 
 Bootstrap Statistics: 
  original     bias         std_error    CI_lower     CI_upper  
- +0.2175      +0.02466     +0.2762      -0.3036      +0.6140    
- -0.3347      -0.01186     +0.2594      -0.8400      +0.03226</pre>
+ +0.2704      -0.002971    +0.2338      -0.1292      +0.6239    
+ -0.3695      -0.01173     +0.2200      -0.7058      +0.01681</pre>
 </div>
 
 <h3><a name="9">Demonstration 9</a></h3>

docs/function/bootlm.html

@@ -417,7 +417,7 @@ <h2>bootlm</h2>
        - 'fpr': The minimum false positive risk (FPR) for each p-value
        - 'N': The number of independent sampling units used to compute CIs
        - 'prior': The prior used for Bayesian bootstrap. This will return a
-                  scalar for regression coeefficients, or a P x 1 or P x 2
+                  scalar for regression coefficients, or a P x 1 or P x 2
                   matrix for estimated marginal means or posthoc tests
                   respectively, where P is the number of parameter estimates.
        - 'levels': A cell array with the levels of each predictor.

docs/function/bootmode.html

@@ -149,9 +149,9 @@ <h3><a name="1">Demonstration 1</a></h3>
 <p>Produces the following output</p>
 <pre class="example">ans = Summary of results:
 
-ans = H1 is 1 with p = 0.0005 so reject the null hypothesisthat there is 1 mode
+ans = H1 is 1 with p = 0.001 so reject the null hypothesisthat there is 1 mode
 
-ans = H2 is 0 with p = 0.332 so accept the null hypothesis that there are 2 modes</pre>
+ans = H2 is 0 with p = 0.327 so accept the null hypothesis that there are 2 modes</pre>
 </div>
 
 <p>Package: <a href="../index.html">statistics-resampling</a></p>

docs/function/bootwild.html

@@ -218,8 +218,8 @@ <h3><a name="2">Demonstration 2</a></h3>
 
 Test Statistics: 
  original     std_err      CI_lower     CI_upper     t-stat      p-val     FPR
- +175.5       +2.563       +170.0       +181.0       +68.5       <.001    .010
- +0.1904      +0.08460     +0.008008    +0.3728      +2.25        .041    .262</pre>
+ +175.5       +2.563       +169.8       +181.2       +68.5       <.001    .010
+ +0.1904      +0.08460     +0.003534    +0.3773      +2.25        .047    .280</pre>
 </div>
 
 <p>Package: <a href="../index.html">statistics-resampling</a></p>

docs/function/images/boot1way_701.png

@@ -146,8 +146,8 @@ <h3><a name="2">Demonstration 2</a></h3>
 <p>Produces the following output</p>
 <pre class="example">pval =
 
-      0.54267
-       0.0002
+      0.53148
+   0.00049014
 
 stat =
 
@@ -173,7 +173,7 @@ <h3><a name="3">Demonstration 3</a></h3>
  % of standardized x and y values.
  [pval, stat] = randtest (X, Y, 5000, @cor)</pre>
 <p>Produces the following output</p>
-<pre class="example">pval = 0.00036681
+<pre class="example">pval = 0.0002
 stat = 0.72317</pre>
 </div>
 

docs/function/images/boot1way_801.png

@@ -162,9 +162,9 @@ <h3><a name="1">Demonstration 1</a></h3>
                            @(A, B) log (var (A) ./ var (B)))
 </pre>
 <p>Produces the following output</p>
-<pre class="example">pval = 0.3584
-pval = 0.2746
-pval = 0.3296</pre>
+<pre class="example">pval = 0.3668
+pval = 0.2698
+pval = 0.30905</pre>
 </div>
 
 <h3><a name="2">Demonstration 2</a></h3>

docs/function/randtest.html

@@ -1,5 +1,5 @@
 <deployment-project plugin="plugin.toolbox" plugin-version="1.0">
-  <configuration build-checksum="2330128564" file="Y:\Documents\GitHub\statistics-resampling\matlab\statistics-resampling.prj" location="Y:\Documents\GitHub\statistics-resampling\matlab" name="statistics-resampling" target="target.toolbox" target-name="Package Toolbox">
+  <configuration build-checksum="3306453136" file="Y:\Documents\GitHub\statistics-resampling\matlab\statistics-resampling.prj" location="Y:\Documents\GitHub\statistics-resampling\matlab" name="statistics-resampling" target="target.toolbox" target-name="Package Toolbox">
     <param.appname>statistics-resampling</param.appname>
     <param.authnamewatermark>Andrew Penn</param.authnamewatermark>
     <param.email>[email protected]</param.email>