Package: statistics-resampling
diff --git a/docs/function/bootknife.html b/docs/function/bootknife.html index 19644c57..fb4739c0 100644 --- a/docs/function/bootknife.html +++ b/docs/function/bootknife.html @@ -3,7 +3,7 @@ - + @@ -223,11 +223,11 @@The following code
-
-
- % Calculating confidence intervals for the coefficients from logistic
- % regression using an example with an ordinal response from:
- % https://uk.mathworks.com/help/stats/mnrfit.html
-
- %>>>>>>>>> This code block must be run first in Octave only >>>>>>>>>>>>
-
- try
- pkg load statistics
- load carbig
- info = ver;
- if ( str2num ({info.Version}{strcmp({info.Name},'statistics')}(1:3)) < 1.5)
- error ('statistics package version must be > 1.5')
- end
- if (~ exist ('mnrfit', 'file'))
- % Octave Statistics package does not currently have the mnrfit function,
- % so we will use it's logistic_regression function for fitting ordinal
- % models instead.
- function [B, DEV] = mnrfit (X, Y, varargin)
- % Note that if the outcome has more than two levels, the
- % logistic_regression function is only suitable when the
- % outcome is ordinal, so we would need to use append 'model',
- % 'ordinal' as a name-value pair in MATLAB when executing
- % it's mnrfit function (see below)
- [INTERCEPT, SLOPE, DEV] = logistic_regression (Y - 1, X, false);
- B = cat (1, INTERCEPT, SLOPE);
- end
- end
- stats_pkg = true;
- catch
- stats_pkg = false;
- fprintf ('\nSkipping this demo...')
- fprintf ('\nRequired features of the statistics package not found.\n\n');
- end
-
- %<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
-
- if (stats_pkg)
-
- %>>>>>>>>>>>>>>>>>>> This code block is the demo >>>>>>>>>>>>>>>>>>>>>>
-
- % This demo requires the statistics package in Octave (equivalent to
- % the Statistics and Machine Learning Toolbox in Matlab)
-
- % Create the dataset
- load carbig
- X = [Acceleration Displacement Horsepower Weight];
-
- % The responses 1 - 4 correspond to the following classification:
- % 1: 9 - 19 miles per gallon
- % 2: 19 - 29 miles per gallon
- % 3: 29 - 39 miles per gallon
- % 4: 39 - 49 miles per gallon
- miles = [1,1,1,1,1,1,1,1,1,1,NaN,NaN,NaN,NaN,NaN,1,1,NaN,1,1,2,2,1,2, ...
- 2,2,2,2,2,2,2,1,1,1,1,2,2,2,2,NaN,2,1,1,2,1,1,1,1,1,1,1,1,1, ...
- 2,2,1,2,2,3,3,3,3,2,2,2,2,2,2,2,1,1,1,1,1,1,1,1,1,2,1,1,1,1, ...
- 1,2,2,2,2,2,2,2,2,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,1,1,1, ...
- 1,1,2,2,2,1,2,2,2,1,1,3,2,2,2,1,2,2,1,2,2,2,1,3,2,3,2,1,1,1, ...
- 1,1,1,1,1,3,2,2,3,3,2,2,2,2,2,3,2,1,1,1,1,1,1,1,1,1,1,1,2,2, ...
- 1,3,2,2,2,2,2,2,1,3,2,2,2,2,2,3,2,2,2,2,2,1,1,1,1,2,2,2,2,3, ...
- 2,3,3,2,1,1,1,3,3,2,2,2,1,2,2,1,1,1,1,1,3,3,3,2,3,1,1,1,1,1, ...
- 2,2,1,1,1,1,1,3,2,2,2,3,3,3,3,2,2,2,4,3,3,4,3,2,2,2,2,2,2,2, ...
- 2,2,2,2,1,1,2,1,1,1,3,2,2,3,2,2,2,2,2,1,2,1,3,3,2,2,2,2,2,1, ...
- 1,1,1,1,1,2,1,3,3,3,2,2,2,2,2,3,3,3,3,2,2,2,3,4,3,3,3,2,2,2, ...
- 2,3,3,3,3,3,4,2,4,4,4,3,3,4,4,3,3,3,2,3,2,3,2,2,2,2,3,4,4,3, ...
- 3,3,3,3,3,3,3,3,3,3,3,3,3,2,NaN,3,2,2,2,2,2,1,2,2,3,3,3,2,2, ...
- 2,3,3,3,3,3,3,3,3,3,3,3,2,3,2,2,3,3,2,2,4,3,2,3]';
-
- % Bootsrap confidence intervals for each logistic regression coefficient
- bootknife ({X, miles}, 1999, ...
- @(X, miles) mnrfit (X, miles, 'model', 'ordinal'));
-
- % Where the first 3 rows are the intercept terms, and the last 4 rows
- % are the slope coefficients. For each predictor, the slope coefficient
- % corresponds to how a unit change in the predictor impacts on the odds,
- % which are proportional across the (ordered) catagories, where each
- % log-odds in each case is:
- %
- % ln ( ( P[below] ) / ( P[above] ) )
- %
- % i.e. in mnrfit, the reference class is the higher of the two classes.
- % Therefore, a positive slope value indicates that a unit increase in the
- % predictor increases the odds of running at fewer miles per gallon.
-
- % Note that ordinal and multinomial logistic regression (appropriate
- % for ordinal and nominal responses respectively) would be equivalent
- % for any binary outcome
-
- %<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<<
-
- end
-Produces the following output
-Summary of nonparametric bootstrap estimates of bias and precision -****************************************************************************** - -Bootstrap settings: - Function: @(X, miles) mnrfit (X, miles, 'model', 'ordinal') - Resampling method: Balanced, bootknife resampling - Number of resamples (outer): 1999 - Number of resamples (inner): 0 - Confidence interval (CI) type: Bias-corrected and accelerated (BCa) - Nominal coverage: 95% - -Bootstrap Statistics: - original bias std_error CI_lower CI_upper - -16.69 -0.5265 +2.080 -20.46 -12.37 - -11.72 -0.3715 +1.819 -15.03 -7.926 - -8.061 -0.2689 +1.710 -11.28 -4.570 - +0.1048 +0.005787 +0.09220 -0.09224 +0.2716 - +0.01034 +0.0006836 +0.006734 -0.002759 +0.02344 - +0.06452 +0.002395 +0.01629 +0.03476 +0.09525 - +0.001664 +5.972e-06 +0.0007568 +0.0002100 +0.003176-
The following code
% Air conditioning failure times (x) in Table 1.2 of Davison A.C. and @@ -696,7 +578,7 @@Demonstration 11
gives an example of how 'bootknife' is used.
The following code
diff --git a/docs/function/bootlm.html b/docs/function/bootlm.html index b3a94bd7..57231ac7 100644 --- a/docs/function/bootlm.html +++ b/docs/function/bootlm.html @@ -3,7 +3,7 @@ - + @@ -459,6 +459,16 @@bootlm
model. Computations of the statistics in AOVSTAT are compatible with the 'clustid' and 'blocksz' options. + The bootlm function treats all model predictors as fixed effects during + ANOVA tests. While any type of predictor, be it a fixed effect or + nuisance random effect, can be included in the model as a main effect, + any p-values returned are only meaningful for the main effects and + interactions that involve just fixed effects - same goes for the + p-values and confidence intervals for the associated regression + coefficients. Note also that the bootlm function can be used to compute + p-values for ANOVA with nested data structures by cluster bootstrap + resampling (see the 'clustid' option). + ** See demo 7 for an example of how to obtain results for ANOVA using type II sums-of-squares, which test hypotheses that give results invariant to the order of the predictors, regardless of whether diff --git a/docs/function/bootmode.html b/docs/function/bootmode.html index c7cb49e1..2b3a07a9 100644 --- a/docs/function/bootmode.html +++ b/docs/function/bootmode.html @@ -3,7 +3,7 @@ - + @@ -51,8 +51,8 @@bootmode
Parallel package (in Octave), or the Parallel Computing Toolbox (in Matlab). - '[H, P] = bootmode (X, M, ...)' also returns the p-value of the - bootstrap test. + '[H, P] = bootmode (X, M, ...)' also returns the two-tailed p-value of + the bootstrap hypothesis test. '[H, P, CRITVAL] = bootmode (X, M, ...)' also returns the critical bandwidth (i.e.the smallest bandwidth achievable to obtain a kernel @@ -149,9 +149,9 @@Demonstration 1
Produces the following output
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 = 0.324 so accept the null hypothesis that there are 2 modes+ans = H2 is 0 with p = 0.311 so accept the null hypothesis that there are 2 modes
Package: statistics-resampling
diff --git a/docs/function/bootstrp.html b/docs/function/bootstrp.html index c14cae75..16a25ea1 100644 --- a/docs/function/bootstrp.html +++ b/docs/function/bootstrp.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function/bootwild.html b/docs/function/bootwild.html index 9fb40171..f099dc5d 100644 --- a/docs/function/bootwild.html +++ b/docs/function/bootwild.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function/cor.html b/docs/function/cor.html index 00f34e12..efd5af3c 100644 --- a/docs/function/cor.html +++ b/docs/function/cor.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function/credint.html b/docs/function/credint.html index 27e3098e..22d9d37d 100644 --- a/docs/function/credint.html +++ b/docs/function/credint.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function/deffcalc.html b/docs/function/deffcalc.html index fb742480..612805cf 100644 --- a/docs/function/deffcalc.html +++ b/docs/function/deffcalc.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function/images/boot1way_701.png b/docs/function/images/boot1way_701.png index 16c2cfff..0ce69de9 100644 Binary files a/docs/function/images/boot1way_701.png and b/docs/function/images/boot1way_701.png differ diff --git a/docs/function/images/boot1way_801.png b/docs/function/images/boot1way_801.png index 400c34f4..4e567463 100644 Binary files a/docs/function/images/boot1way_801.png and b/docs/function/images/boot1way_801.png differ diff --git a/docs/function/randtest2.html b/docs/function/randtest2.html index b54c1269..5c3ee797 100644 --- a/docs/function/randtest2.html +++ b/docs/function/randtest2.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function/sampszcalc.html b/docs/function/sampszcalc.html index b63ebf3f..aba0eabd 100644 --- a/docs/function/sampszcalc.html +++ b/docs/function/sampszcalc.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function/smoothmad.html b/docs/function/smoothmad.html index a376f818..4b1db410 100644 --- a/docs/function/smoothmad.html +++ b/docs/function/smoothmad.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function/smoothmedian.html b/docs/function/smoothmedian.html index 26521227..097de22e 100644 --- a/docs/function/smoothmedian.html +++ b/docs/function/smoothmedian.html @@ -3,7 +3,7 @@ - + diff --git a/docs/function_reference.html b/docs/function_reference.html index 554df13d..089802d8 100644 --- a/docs/function_reference.html +++ b/docs/function_reference.html @@ -3,7 +3,7 @@ - + diff --git a/docs/index.html b/docs/index.html index aea19b31..089ea43b 100644 --- a/docs/index.html +++ b/docs/index.html @@ -3,7 +3,7 @@ - + @@ -27,8 +27,8 @@| Package Version: | 5.5.6 |
| Last Release Date: | 2024-01-23 |
| Package Version: | 5.5.7 |
| Last Release Date: | 2024-02-15 |
| Package Author: | Andrew Penn <andy.c.penn@gmail.com> |
| Package Maintainer: | Andrew Penn <andy.c.penn@gmail.com> |
| License: | GPLv3+ |