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26 changes: 13 additions & 13 deletions docs/function/boot.html
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Expand Up @@ -50,7 +50,7 @@ <h2>boot</h2>
'BOOTSAM = boot (..., NBOOT, LOO)' sets the resampling method. If LOO
is false, the resampling method used is balanced bootstrap resampling.
If LOO is true, the resampling method used is balanced bootknife
resampling [4]. The latter involves creating leave-one-out jackknife
resampling [4]. The latter involves creating leave-one-out (jackknife)
samples of size N - 1, and then drawing resamples of size N with
replacement from the jackknife samples, thereby incorporating Bessel's
correction into the resampling procedure. LOO must be a scalar logical
Expand Down Expand Up @@ -118,15 +118,15 @@ <h3><a name="1">Demonstration 1</a></h3>

Columns 1 through 11:

3 2 1 2 3 3 3 3 2 3 1
1 1 1 3 3 2 2 3 1 1 1
2 3 3 2 2 1 3 1 1 1 3
3 2 3 3 2 1 3 1 1 2 2
1 2 2 1 3 2 3 3 3 1 1
2 3 1 1 3 1 1 1 2 1 1

Columns 12 through 20:

2 3 1 2 2 1 1 2 2
3 3 2 2 2 2 2 3 1
3 1 2 1 1 3 3 1 2</pre>
3 3 2 2 2 1 1 3 2
2 1 3 3 3 2 3 3 2
2 1 2 1 2 3 3 2 1</pre>
</div>

<h3><a name="2">Demonstration 2</a></h3>
Expand All @@ -141,15 +141,15 @@ <h3><a name="2">Demonstration 2</a></h3>

Columns 1 through 11:

2 3 1 3 3 2 2 3 1 2 3
3 3 1 2 3 1 2 1 1 2 3
3 3 1 3 1 1 3 1 2 2 1
3 3 2 2 3 2 2 3 2 2 3
2 1 2 2 1 1 2 3 1 3 3
3 1 1 3 3 2 3 1 2 2 1

Columns 12 through 20:

1 2 1 1 2 3 2 2 3
1 3 1 2 3 1 2 1 2
2 2 3 2 3 3 1 1 2</pre>
2 2 1 1 3 1 2 3 1
1 3 3 1 3 1 1 1 2
2 3 1 2 2 3 1 1 3</pre>
</div>

<h3><a name="3">Demonstration 3</a></h3>
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20 changes: 10 additions & 10 deletions docs/function/boot1way.html
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Expand Up @@ -89,14 +89,14 @@ <h2>boot1way</h2>
and how to perform bootstrap iterations using multiple processors (if the
Parallel Computing Toolbox or Octave Parallel package is available). This
argument is a structure with the following recognised fields:
o 'UseParallel': If true, use parallel processes to accelerate
bootstrap computations on multicore machines,
specifically non-vectorized function evaluations,
double bootstrap resampling and jackknife function
evaluations. Default is false for serial computation.
In MATLAB, the default is true if a parallel pool
has already been started.
o 'nproc': nproc sets the number of parallel processes
o 'UseParallel': If true, use parallel processes to accelerate
bootstrap computations on multicore machines,
specifically non-vectorized function evaluations,
double bootstrap resampling and jackknife function
evaluations. Default is false for serial computation.
In MATLAB, the default is true if a parallel pool
has already been started.
o 'nproc': nproc sets the number of parallel processes (optional)

'PVAL = boot1way (DATA, GROUP, ...)' returns the p-value(s) for the
(multiple) two-tailed test(s). Note that the p-value(s) returned are
Expand Down Expand Up @@ -529,7 +529,7 @@ <h3><a name="7">Demonstration 7</a></h3>
-----------------------------------------------------------------------------
| Comparison | Test # | Ref # | Difference | t | p |
|------------|------------|------------|------------|------------|----------|
| 1 | 2 | 1 | +0.08697 | +0.17 | .858 |
| 1 | 2 | 1 | +0.8935 | +2.19 | .043 |*

-----------------------------------------------------------------------------
| GROUP # | GROUP label | N |
Expand Down Expand Up @@ -574,7 +574,7 @@ <h3><a name="8">Demonstration 8</a></h3>
-----------------------------------------------------------------------------
| Comparison | Test # | Ref # | Difference | t | p |
|------------|------------|------------|------------|------------|----------|
| 1 | 2 | 1 | -0.08836 | -0.13 | .837 |
| 1 | 2 | 1 | -0.5111 | -0.52 | .532 |

-----------------------------------------------------------------------------
| GROUP # | GROUP label | N |
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6 changes: 3 additions & 3 deletions docs/function/bootbayes.html
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Expand Up @@ -191,7 +191,7 @@ <h3><a name="1">Demonstration 1</a></h3>

Posterior Statistics:
original bias median stdev CI_lower CI_upper
+184.5 -0.02727 +184.5 1.310 +182.1 +187.3</pre>
+184.5 +0.01968 +184.5 1.300 +182.0 +187.1</pre>
</div>

<h3><a name="2">Demonstration 2</a></h3>
Expand Down Expand Up @@ -228,8 +228,8 @@ <h3><a name="2">Demonstration 2</a></h3>

Posterior Statistics:
original bias median stdev CI_lower CI_upper
+175.5 +0.01959 +175.5 2.479 +170.9 +180.3
+0.1904 -0.001474 +0.1927 0.08174 +0.03816 +0.3526</pre>
+175.5 +0.005319 +175.5 2.374 +171.1 +180.2
+0.1904 +0.0001080 +0.1919 0.07850 +0.03811 +0.3425</pre>
</div>

<p>Package: <a href="../index.html">statistics-resampling</a></p>
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78 changes: 39 additions & 39 deletions docs/function/bootci.html
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Expand Up @@ -109,14 +109,14 @@ <h2>bootci</h2>
and how to perform bootstrap iterations using multiple processors (if the
Parallel Computing Toolbox or Octave Parallel package is available). This
argument is a structure with the following recognised fields:
<> 'UseParallel': If true, use parallel processes to accelerate
bootstrap computations on multicore machines,
specifically non-vectorized function evaluations,
double bootstrap resampling and jackknife function
evaluations. Default is false for serial computation.
In MATLAB, the default is true if a parallel pool
has already been started.
<> 'nproc': nproc sets the number of parallel processes
<> 'UseParallel': If true, use parallel processes to accelerate
bootstrap computations on multicore machines,
specifically non-vectorized function evaluations,
double bootstrap resampling and jackknife function
evaluations. Default is false for serial computation.
In MATLAB, the default is true if a parallel pool
has already been started.
<> 'nproc': nproc sets the number of parallel processes (optional)

'[CI, BOOTSTAT] = bootci (...)' also returns the bootstrap statistics
used to calculate the confidence intervals CI.
Expand Down Expand Up @@ -186,8 +186,8 @@ <h3><a name="1">Demonstration 1</a></h3>
<p>Produces the following output</p>
<pre class="example">ci =

23.895
34.598</pre>
23.719
34.353</pre>
</div>

<h3><a name="2">Demonstration 2</a></h3>
Expand All @@ -206,8 +206,8 @@ <h3><a name="2">Demonstration 2</a></h3>
<p>Produces the following output</p>
<pre class="example">ci =

24
34.118</pre>
23.951
34.56</pre>
</div>

<h3><a name="3">Demonstration 3</a></h3>
Expand All @@ -227,8 +227,8 @@ <h3><a name="3">Demonstration 3</a></h3>
<p>Produces the following output</p>
<pre class="example">ci =

24.924
37.101</pre>
24.831
36.975</pre>
</div>

<h3><a name="4">Demonstration 4</a></h3>
Expand All @@ -247,8 +247,8 @@ <h3><a name="4">Demonstration 4</a></h3>
<p>Produces the following output</p>
<pre class="example">ci =

99.352
237.73</pre>
96.237
235.64</pre>
</div>

<h3><a name="5">Demonstration 5</a></h3>
Expand All @@ -267,8 +267,8 @@ <h3><a name="5">Demonstration 5</a></h3>
<p>Produces the following output</p>
<pre class="example">ci =

116.14
265.21</pre>
114.34
257.98</pre>
</div>

<h3><a name="6">Demonstration 6</a></h3>
Expand All @@ -288,8 +288,8 @@ <h3><a name="6">Demonstration 6</a></h3>
<p>Produces the following output</p>
<pre class="example">ci =

114.58
298.41</pre>
112.56
297.01</pre>
</div>

<h3><a name="7">Demonstration 7</a></h3>
Expand All @@ -309,8 +309,8 @@ <h3><a name="7">Demonstration 7</a></h3>
<p>Produces the following output</p>
<pre class="example">ci =

110.15
272.46</pre>
114.63
272.39</pre>
</div>

<h3><a name="8">Demonstration 8</a></h3>
Expand All @@ -331,8 +331,8 @@ <h3><a name="8">Demonstration 8</a></h3>
<p>Produces the following output</p>
<pre class="example">ci =

0.51805
0.85978</pre>
0.50486
0.8608</pre>
</div>

<h3><a name="9">Demonstration 9</a></h3>
Expand Down Expand Up @@ -439,13 +439,13 @@ <h3><a name="9">Demonstration 9</a></h3>
<p>Produces the following output</p>
<pre class="example">ans =

-16.69 -20.545 -12.638
-11.721 -15.163 -8.0707
-8.0606 -11.384 -4.5899
0.10476 -0.072888 0.28242
0.010336 -0.0020222 0.023297
0.06452 0.032508 0.094107
0.0016638 0.0002219 0.0030662</pre>
-16.69 -20.563 -12.28
-11.721 -15.162 -7.7424
-8.0606 -11.43 -4.392
0.10476 -0.079726 0.28251
0.010336 -0.002213 0.023716
0.06452 0.032564 0.095997
0.0016638 0.00011273 0.0030787</pre>
</div>

<h3><a name="10">Demonstration 10</a></h3>
Expand All @@ -466,8 +466,8 @@ <h3><a name="10">Demonstration 10</a></h3>
<p>Produces the following output</p>
<pre class="example">ci =

-0.16358 -0.84894
0.71954 0.45924</pre>
-0.1715 -1.3765
0.88634 0.45191</pre>
</div>

<h3><a name="11">Demonstration 11</a></h3>
Expand Down Expand Up @@ -574,12 +574,12 @@ <h3><a name="11">Demonstration 11</a></h3>
%
% method | 0.05 | 0.95 | length | shape |
% -------------------|--------|--------|--------|-------|
% ci1 - normal | 109.5 | 246.8 | 137.3 | 1.21 |
% ci2 - percentile | 97.7 | 234.9 | 137.2 | 0.86 |
% ci3 - basic | 108.2 | 245.4 | 137.2 | 1.17 |
% ci4 - BCa | 116.0 | 260.3 | 144.3 | 1.60 |
% ci5 - bootstrap-t | 112.8 | 289.8 | 177.0 | 2.02 |
% ci6 - calibrated | 115.2 | 278.7 | 163.5 | 1.90 |
% ci1 - normal | 108.9 | 247.4 | 138.5 | 1.22 |
% ci2 - percentile | 98.2 | 235.1 | 136.9 | 0.87 |
% ci3 - basic | 108.0 | 244.8 | 136.9 | 1.15 |
% ci4 - BCa | 116.2 | 259.6 | 143.4 | 1.60 |
% ci5 - bootstrap-t | 114.0 | 289.5 | 175.5 | 2.05 |
% ci6 - calibrated | 115.3 | 276.9 | 161.6 | 1.87 |
% -------------------|--------|--------|--------|-------|
% parametric - exact | 118.4 | 305.2 | 186.8 | 2.52 |
%
Expand Down
30 changes: 15 additions & 15 deletions docs/function/bootclust.html
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Expand Up @@ -187,11 +187,11 @@ <h3><a name="1">Demonstration 1</a></h3>
Number of resamples: 1999
Number of data rows in each block: 1
Confidence interval (CI) type: Expanded bias-corrected and accelerated (BCa)
Nominal coverage (and the percentiles used): 95% (1.4%, 97.7%)
Nominal coverage (and the percentiles used): 95% (1.1%, 97.3%)

Bootstrap Statistics:
original bias std_error CI_lower CI_upper
+29.65 +1.776e-14 +2.573 +23.98 +34.67</pre>
+29.65 +3.197e-14 +2.641 +23.21 +34.48</pre>
</div>

<h3><a name="2">Demonstration 2</a></h3>
Expand Down Expand Up @@ -223,7 +223,7 @@ <h3><a name="2">Demonstration 2</a></h3>

Bootstrap Statistics:
original bias std_error CI_lower CI_upper
+29.65 -0.03233 +2.892 +23.14 +35.97</pre>
+29.65 -0.03725 +2.871 +22.98 +36.10</pre>
</div>

<h3><a name="3">Demonstration 3</a></h3>
Expand Down Expand Up @@ -254,7 +254,7 @@ <h3><a name="3">Demonstration 3</a></h3>

Bootstrap Statistics:
original bias std_error CI_lower CI_upper
+171.5 -6.406 +41.53 +99.13 +234.2</pre>
+171.5 -6.867 +42.28 +96.02 +235.0</pre>
</div>

<h3><a name="4">Demonstration 4</a></h3>
Expand Down Expand Up @@ -286,7 +286,7 @@ <h3><a name="4">Demonstration 4</a></h3>

Bootstrap Statistics:
original bias std_error CI_lower CI_upper
+171.5 -8.995 +32.96 +106.1 +215.3</pre>
+171.5 -9.729 +34.13 +102.0 +214.6</pre>
</div>

<h3><a name="5">Demonstration 5</a></h3>
Expand All @@ -312,11 +312,11 @@ <h3><a name="5">Demonstration 5</a></h3>
Number of resamples: 1999
Number of data rows in each block: 1
Confidence interval (CI) type: Bias-corrected and accelerated (BCa)
Nominal coverage (and the percentiles used): 90% (12.1%, 98.7%)
Nominal coverage (and the percentiles used): 90% (11.7%, 98.6%)

Bootstrap Statistics:
original bias std_error CI_lower CI_upper
+171.5 -6.855 +41.69 +115.4 +263.0</pre>
+171.5 -6.427 +42.26 +115.1 +260.9</pre>
</div>

<h3><a name="6">Demonstration 6</a></h3>
Expand All @@ -343,11 +343,11 @@ <h3><a name="6">Demonstration 6</a></h3>
Resampling method: Balanced, bootstrap cluster resampling
Number of resamples: 1999
Confidence interval (CI) type: Bias-corrected and accelerated (BCa)
Nominal coverage (and the percentiles used): 90% (14.6%, 98.9%)
Nominal coverage (and the percentiles used): 90% (12.4%, 98.6%)

Bootstrap Statistics:
original bias std_error CI_lower CI_upper
+171.5 -9.973 +33.87 +125.3 +232.9</pre>
+171.5 -9.104 +33.56 +121.9 +229.1</pre>
</div>

<h3><a name="7">Demonstration 7</a></h3>
Expand Down Expand Up @@ -376,8 +376,8 @@ <h3><a name="7">Demonstration 7</a></h3>

Bootstrap Statistics:
original bias std_error CI_lower CI_upper
+0.04006 -0.01294 +0.2088 -0.3053 +0.3697
+0.1410 +0.0005343 +0.1810 -0.1187 +0.4558</pre>
-0.1741 +0.01486 +0.2484 -0.5881 +0.2297
+0.1214 -0.01454 +0.2770 -0.3540 +0.5406</pre>
</div>

<h3><a name="8">Demonstration 8</a></h3>
Expand Down Expand Up @@ -406,8 +406,8 @@ <h3><a name="8">Demonstration 8</a></h3>

Bootstrap Statistics:
original bias std_error CI_lower CI_upper
-0.1446 +0.004816 +0.2655 -0.6247 +0.2453
-0.3187 +0.02024 +0.2593 -0.7709 +0.08425</pre>
-0.06640 -0.007945 +0.3481 -0.6557 +0.4922
-0.2947 -0.009006 +0.2996 -0.7190 +0.2647</pre>
</div>

<h3><a name="9">Demonstration 9</a></h3>
Expand All @@ -434,11 +434,11 @@ <h3><a name="9">Demonstration 9</a></h3>
Resampling method: Balanced, bootstrap cluster resampling
Number of resamples: 1999
Confidence interval (CI) type: Bias-corrected and accelerated (BCa)
Nominal coverage (and the percentiles used): 95% (2.0%, 97.0%)
Nominal coverage (and the percentiles used): 95% (1.8%, 96.7%)

Bootstrap Statistics:
original bias std_error CI_lower CI_upper
+0.7764 -0.02443 +0.1439 +0.4074 +0.9985</pre>
+0.7764 -0.02529 +0.1467 +0.3886 +0.9972</pre>
</div>

<h3><a name="10">Demonstration 10</a></h3>
Expand Down
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