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https://github.com/karoliskoncevicius/matrixtests

R package for computing multiple hypothesis tests on rows/columns of a matrix or a data.frame
https://github.com/karoliskoncevicius/matrixtests

anova fast hypothesis-testing matrix package r rows t-test wilcoxon-test

Last synced: 4 days ago
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R package for computing multiple hypothesis tests on rows/columns of a matrix or a data.frame

Host: GitHub
URL: https://github.com/karoliskoncevicius/matrixtests
Owner: karoliskoncevicius
Created: 2017-03-14T21:53:02.000Z (over 7 years ago)
Default Branch: master
Last Pushed: 2024-06-07T16:18:32.000Z (5 months ago)
Last Synced: 2024-10-11T18:48:25.878Z (25 days ago)
Topics: anova, fast, hypothesis-testing, matrix, package, r, rows, t-test, wilcoxon-test
Language: R
Homepage: https://cran.r-project.org/web/packages/matrixTests/index.html
Size: 608 KB
Stars: 36
Watchers: 4
Forks: 5
Open Issues: 18
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml

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README

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# Matrix Tests #

A package dedicated to running multiple statistical hypothesis tests on rows and columns of matrices.

![illustration](http://karolis.koncevicius.lt/data/matrixtests/illustration.png)

## Goals ##

1. Fast execution via vectorization.

2. Convenient and detailed output format.

3. Compatibility with tests implemented in base R.

4. Careful handling of missing values and edge cases.

## Examples ##

#### 1. Bartlett's test on columns ####

Bartlett's test on every column of iris dataset using Species as groups:

```r

col_bartlett(iris[,-5], iris$Species)

```

```

             obs.tot obs.groups var.pooled df statistic                pvalue

Sepal.Length     150          3 0.26500816  2 16.005702 0.0003345076070163084

Sepal.Width      150          3 0.11538776  2  2.091075 0.3515028004158132768

Petal.Length     150          3 0.18518776  2 55.422503 0.0000000000009229038

Petal.Width      150          3 0.04188163  2 39.213114 0.0000000030547839322

```

#### 2. Welch t-test on rows ####

Welch t-test performed on each row of 2 large (million row) matrices:

```r

X <- matrix(rnorm(10000000), ncol = 10)

Y <- matrix(rnorm(10000000), ncol = 10)

row_t_welch(X, Y)  # running time: 2.4 seconds

```

Confidence interval computations can be turned-off for further increase in speed:

```r

row_t_welch(X, Y, conf.level = NA)  # running time: 1 second

```

## Available Tests ##

|           Variant                |           Name                        |           Function                 |

|----------------------------------|---------------------------------------|------------------------------------|

| **Location tests (1 group)**     | Single sample Student's t.test        | `row_t_onesample`                  |

|                                  | Single sample Wilcoxon's test         | `row_wilcoxon_onesample`           |

| **Location tests (2 groups)**    | Equal variance Student's t.test       | `row_t_equalvar`                   |

|                                  | Welch adjusted Student's t.test       | `row_t_welch`                      |

|                                  | Two sample Wilcoxon's test            | `row_wilcoxon_twosample`           |

| **Location tests (paired)**      | Paired Student's t.test               | `row_t_paired`                     |

|                                  | Paired Wilcoxon's test                | `row_wilcoxon_paired`              |

| **Location tests (2+ groups)**   | Equal variance oneway anova           | `row_oneway_equalvar`              |

|                                  | Welch's oneway anova                  | `row_oneway_welch`                 |

|                                  | Kruskal-Wallis test                   | `row_kruskalwallis`                |

|                                  | van der Waerden's test                | `row_waerden`                      |

| **Scale tests (2 groups)**       | F variance test                       | `row_f_var`                        |

| **Scale tests (2+ groups)**      | Bartlett's test                       | `row_bartlett`                     |

|                                  | Fligner-Killeen test                  | `row_flignerkilleen`               |

|                                  | Levene's test                         | `row_levene`                       |

|                                  | Brown-Forsythe test                   | `row_brownforsythe`                |

| **Association tests**            | Pearson's correlation test            | `row_cor_pearson`                  |

| **Periodicity tests**            | Cosinor                               | `row_cosinor`                      |

| **Distribution tests**           | Kolmogorov-Smirnov test               | `row_kolmogorovsmirnov_twosample`  |

| **Normality tests**              | Jarque-Bera test                      | `row_jarquebera`                   |

|                                  | Anderson-Darling test                 | `row_andersondarling`              |

## Further Information ##

For more information please refer to the [Wiki](https://github.com/karoliskoncevicius/matrixTests/wiki) page:

1. [Installation Instructions](https://github.com/karoliskoncevicius/matrixTests/wiki/Installation)

2. [Design Decisions](https://github.com/karoliskoncevicius/matrixTests/wiki/Design-Decisions)

3. [Speed Benchmarks](https://github.com/karoliskoncevicius/matrixTests/wiki/Benchmarks)

4. [Bug Fixes and Improvements to Base R](https://github.com/karoliskoncevicius/matrixTests/wiki/Bug-Fixes-and-Improvements-to-Base-R)

## See Also ##

### Literature ###

**Computing thousands of test statistics simultaneously in R**, *Holger Schwender, Tina Müller*.\

Statistical Computing & Graphics. Volume 18, No 1, June 2007.

### Packages ###

CRAN:

1. `ttests()` in the [**Rfast**](https://CRAN.R-project.org/package=Rfast) package.

2. `row.ttest.stat()` in the [**metaMA**](https://CRAN.R-project.org/package=metaMA) package.

3. `MultiTtest()` in the [**ClassComparison**](https://CRAN.R-project.org/package=ClassComparison) package.

4. `bartlettTests()` in the [**heplots**](https://CRAN.R-project.org/package=heplots) package.

5. `harmonic.regression()` in the [**HarmonicRegression**](https://CRAN.R-project.org/package=HarmonicRegression) package.

BioConductor:

1. `lmFit()` in the [**limma**](https://bioconductor.org/packages/release/bioc/html/limma.html) package.

2. `rowttests()` in the [**genefilter**](https://bioconductor.org/packages/release/bioc/html/genefilter.html) package.

3. `mt.teststat()` in the [**multtest**](https://www.bioconductor.org/packages/release/bioc/html/multtest.html) package.

4. `row.T.test()` in the [**HybridMTest**](https://www.bioconductor.org/packages/release/bioc/html/HybridMTest.html) package.

5. `rowTtest()` in the [**viper**](https://bioconductor.org/packages/release/bioc/html/viper.html) package.

6. `lmPerGene()` in the [**GSEAlm**](https://www.bioconductor.org/packages/release/bioc/html/GSEAlm.html) package.

GitHub:

1. `rowWilcoxonTests()` in the [**sanssouci**](https://github.com/pneuvial/sanssouci) package.

2. `matrix.t.test()` in the [**pi0**](https://github.com/gitlongor/pi0) package.

3. `wilcoxauc()` in the [**presto**](https://github.com/immunogenomics/presto) package.