Anderson-Darling Goodness Of Fit Test to Inverse Gaussian Distbtn

Tests M random samples of N random vars to determine if they are from Inverse Gaussian distbtn.

This program is based on the method published by O'Reilly & Rueda (see program for more details for reference). Confidence level (i.e. alpha value) is chosen,and if the number of AD test stats

AnDarksamtest

Anderson-Darling k-sample procedure to test whether k sampled populations are identical.

Anderson and Darling (1952, 1954) introduced a goodness-of-fit statistic to test the hypothesis that a random sample comes from a continuous population with a specified distribution function. It is a

AnDartest

Anderson-Darling test for assessing normality of a sample data.

The Anderson-Darling test (Anderson and Darling, 1952) is used to test if a sample of data comes from a specific distribution. It is a modification of the Kolmogorov-Smirnov (K-S) test and gives more

AnDarWtest

Anderson-Darling test for assessing Weibull distribution of a sample data.

The Anderson-Darling test (Anderson and Darling, 1952) is used to test if a sample of data comes from a specific distribution. It is a modification of the Kolmogorov-Smirnov (K-S) test and gives more

Modified Anderson-Darling test for Extreme Value Distribution for maxima

ModifiedADforGumbel calculates Modified Anderson-Darling test statistic and estimates p-value

ModifiedADforGumbel calculated Modified Anderson-Darling test statistic and estimates p-value for Extreme Value distribution (GEV tYpe I) for maxima. The EV parameters are eslimated by the Method of

AnDarexptest

Anderson-Darling test for assessing exponential distribution of a sample data.

The Anderson-Darling test (Anderson and Darling, 1952) is used to test if a sample of data comes from a specific distribution. It is a modification of the Kolmogorov-Smirnov (K-S) test and gives more

Weibull fit tests

3 goodnes of fit tests for thw Weibull: Anderson-Darling, Chi-squared and graphic

3 goodnes of fit tests for thw Weibull: Anderson-Darling, Chi-squared and graphic

Normality test package

This function calculates p-values for ten well-known normality tests.

)), Anderson-Darling (AD) test, Cramer-Von Mises (CvM) test, Shapiro-Wilk (SW) test, Shapiro-Francia (SF) test, Jarque-Bera (JB) test, D’Agostino and Pearson (DAP) test. Tests are not meant for big data. Most tests does

Shapiro-Wilk and Shapiro-Francia normality tests.

Shapiro-Wilk & Shapiro-Francia parametric hypothesis test of composite normality.

Shapiro-Wilk parametric hypothesis test of composite normality, for sample size 3<= n <= 5000. Based on Royston R94 algorithm.This test also performs the Shapiro-Francia normality test for

higham/anderson-accel-ncm

Anderson acceleration of the alternating projections method for the nearest correlation matrix.

MATLAB codes for Anderson acceleration for the alternating projectionsmethod for the nearest correlation matrix problem, based on the paperNicholas J. Higham and Nataša Strabić. Anderson

SafeML: Safety Monitoring of Machine Learning Classifiers

Exploring techniques for estimating the safety of machine learning classifiers

detection of simulated network traffic, using distributional shift detection measures including the Kolmogorov-Smirnov, Kuiper, Anderson-Darling, Wasserstein and mixed Wasserstein-Anderson-Darling measures

ECDF-based Distance Measure Algorithms

A set of functions for well-known Empirical cumulative distribution function (ECDF)-based distance measures.

DistanceAnderson-Darling DistanceKolmogorov Smirnov DistanceCramer von Mises DistanceKuiper DistanceWasserstein-Anderson-Darling DistanceRelated WorksThe code has been converted to MATLAB from "twosamples" library of R

Normality Test Explorer

Live Script exploring tests of an empirical distribution for normality.

Anderson-Darling test and a Kolmogorov-Smirnov test for normality.This script may interest students and educators in physics and other STEM fields. Sliders are provided to adjust the empirical distribution

AI Verification Library for Deep Learning Toolbox

Verify and test robustness of deep learning networks, deploy with confidence

AI Verification Library for Deep Learning Toolbox allows you to verify and test properties of deep learning networks, and deploy these models with confidence.Use this library to:Verify network

test-t

Calculate the Student t Test for unequal or equal samples size, unpaired or paired samples.

Student's t test for unpaired or paired samples.This file is applicable for equal or unequal sample sizes; for paired or unpaired samples. When the test is unpaired, the Fisher-Snedecor F-test

INPOLY: A fast points-in-polygon test

A fast test to determine point inclusion for general polygonal geometries.

examplepolydemo(2); % multiply-connected domainspolydemo(3); % speed comparisonINPOLY implements a sorted 'crossing-number' test designed to achieve fast performance for complex inputs. Given a configuration with N

Cramer-von Mises goodness-of-fit test for simple Null Hypothesis

Estimates p-value of acceptance of a simple H0: "CDF with parameters estimated of given sample"

puts the same weight on an entire range of X (unlike the Anderson-Darling test putting more weight on tails of a distribution).

Zone plate test image

MATLAB function to create a zone plate test image

and also for testing the anti-aliasing capability of image resizing methods.For more

Testing Safety Critical Control Systems

This is a presentation on testing of safety critical control systems.

This has a presentation on testing Safety Critical Control Systems and a brief introduction to Formal Methods

Jonckheere-Terpstra test on trend

A nonparametric Test for Trend

Perform the Jonckheere-Terpstra test on trend.There are situations in which treatments are ordered in some way, for example the increasing dosages of a drug. In these cases a test with the more

Communications Toolbox Support Package for Analog Devices ADALM-Pluto Radio

Prototype and test software-defined radio (SDR) systems using ADALM-PLUTO with MATLAB and Simulink

use ADALM-Pluto Radio as a standalone peripheral for live RF data I/O using MATLAB functions or Simulink blocks. This lets you quickly test your transmitter and receiver designs under real-world

fdr_bh

Benjamini & Hochberg/Yekutieli false discovery rate control procedure for a set of statistical tests

Executes the Benjamini & Hochberg (1995) procedure for controlling the false discovery rate (FDR) of a family of hypothesis tests. FDR is the expected proportion of rejected hypotheses that are

Cuzick's test for trend

A Wilcoxon-Type Test for Trend

Perform the Cuzick's test on trend.This function provides a Wilcoxon-type test for trend across a group of three or more independent random samples. Assumptions: Data must be at least ordinal

Normal Distribution Analyser

This function automatically validates the normality of your data using 9 appropriate statistical and visualization techniques.

your data against renowned statistical tests including Shapiro-Wilk, Kolmogorov-Smirnov, Anderson-Darling, Jarque-Bera, and Lilliefors tests. The function compiles resulting P-values in a concise table

F-Test

Test whether addition of model parameters is warranted by improvement of data misfits.

This function uses an F-test to determine the likelihood that an observed improvement of a fit to data warrants the use of additional parameters.Usage:>> [ p, Fstat, df1, df2 ] =

Automated Driving Toolbox Test Suite for Euro NCAP Protocols

Automatically generate seed scenarios for the Euro NCAP test protocols and generate scenario variants.

The Automated Driving Toolbox™ Test Suite for Euro NCAP^® Protocols support package enables you to automatically generate specifications for various Euro NCAP^® tests, which include safety assessments

Sinusoidal Signal Significance Explorer

Live Script illustrating hypothesis tests with a noisy sinusoidal signal.

This Live Script illustrates various hypothesis tests (Lillifors, Jarque-Bera, Anderson-Darling, Kolmogorov–Smirnov, Wald–Wolfowitz runs test, autocorrelation Ljung-Box Q-test, and Fisher

NI USRP Radio Support from Wireless Testbench

Test wideband wireless systems and perform spectrum monitoring

spectrum monitoring and the testing of wideband wireless systems. Additionally, high-rate signal capture enables data set creation for the training of deep-learning models for wireless applications.You can

McNemar test

Perform the McNemar test on a 2x2 matrix

Permorm McNemar's chi square on a 2x2 matrixIn statistics, McNemar's test is a non-parametric method used on nominaldata to determine whether the row and column marginal frequencies areequal. It is

NPCR and UACI measurements with statistical tests

Randomness measure of 'number of pixel changing rate' and 'unified average changed intensity'

This single m file implements the randomness measure of NPCR and UACI, and produces the classic quantitative scores and the new qualitative randomness test p-Vals.

Simulink Test Support Package for ASAM XIL Standard

This support package adds ASAM XIL Standard support to the Test Manager in Simulink Test.

The Simulink^® Test™ Support Package for ASAM^® XIL Standard implements the ASAM XIL API, which is a standard that defines communication between test automation tools, such as Simulink Test, and test

Permutation Test

A permutation test (aka randomization test) for MATLAB, testing for a difference in means between two samples.

A permutation test (aka randomization test) for MATLAB, testing for a difference in means between two samples. It supports one- and two-tailed tests, and returns a p-value, the observed difference

Stroop Test

Test two key cognitive skills, response inhibition and selective attention

Because most people’s automatic response is to read a word, the Stroop Test is a classic test of response inhibition. This skill involves responding quickly while avoiding incorrect impulses that may

mwwtest

Mann-Whitney-Wilcoxon non parametric test for two unpaired groups.

This file execute the non parametric Mann-Whitney-Wilcoxon test to evaluate thedifference between unpaired samples. If the number of combinations is less than20000, the algorithm calculates the exact

0 - 1 test for chaos

Implements the Gottwald - Melbourne 0 - 1 test for chaos

In 2004 Georg Gottwald and Ian Melbourne introduced a new test for chaos (Proc. Roy. Soc. A 460, 603–611). The input is any time series, that may come from a discrete map, a differential equation or

Partest

The test calculate the performance of a clinical test based on the Bayes theorem

) - Test Accuracy - Mis-classification Rate - F-Measure - Test bias - Error odds ratio - Diagnostic odds ratio - Discriminant Power Example: x=[731 270;78 1500

randanova1

Perform permutation test to estimate P-value for one-way ANOVA

Follows Anderson (doi:10.1139/cjfas-58-3-626) to estimate P-values for one-way ANOVA using permutation of data over grouping variable.

Small Signal Stability

Small signal stability

Seasonal Kendall Test with Slope for Serial Dependent Data

Seasonal trends using tau-a,b and seasonal slope with intervals, accounts for serial dependence.

Seasonal Kendall Trend Test for Data with and without Searial Dependance.Tau-b seasonal: takes into account ties (and multiple observations, except, the data are preprocessed in a subfucntion and

Dunn's test

Dunn's procedure for multiple, non parametric, comparisons

Dunn's test is the not parametric analog of Holm-Sidak multiple t-test. When you use the Kruskal-Wallis test, you know if there is a difference among your groups, but you can't apply the KWtest for

Controllability Test

Matrix Controllability Test

Matrix Controllability Test

Analyzing Tire Test Data

Tire test data is processed and Magic Formula coefficients are calculated.

TireDataAnalysis.mlx processes tire test data from acceleration and brake as well as cornering tests and returns the Pacejka’s Magic Formula coefficients for both a longitudinal and lateral model.

Design and Test Lithium Ion Battery Management Algorithms

This example project can be used as a reference design to get started with designing Battery Management System with MATLAB and Simulink.

Management - Over/Under Voltage, Over Current, Over Temperature etc. 5. Charge and Discharge Current Limit Calculations To design and test these algorithms, project also includes files for 1. Li-ion Battery

Generation of Random Variates

generates random variates from over 870 univariate distributions

Prandtl-Meyer expansion wave solver

Numerical solution of a Prandtl-Meyer expansion wave flow field based on Anderson's CFD book

applications" from J.D.Anderson. As a result, this code might be useful for those trying to solve the problem, but also for anyone who is interested in supersonic aerodynamics.

chi2test

The chi-squared test.

Usage: [p, Q]= chi2test(x) The chi-squared test. Given a number of samples this function tests the hypothesis that the samples are independent. If Q > chi2(p, nu), the hypothesis is rejected

Tests to Identify Outliers in Data Series

This document includes several statistical tests to identify outliers in data series.

identify suspicious observations that would require further analysis and also tests to determine if some observations are outliers. Nevertheless, it would be dangerous to blindly accept the result of a test

Hybrid AC/DC & DC microgrid test system simulation

In this model, a Microgrid test system based on the 14-busbar IEEE distribution system is proposed.

Hz.This test system simulation includes:• One diesel generator,• Two photovoltaic (PV) systems,• Two battery energy storage system,• Various linear and non-linear loads.Additionally, the DC microgrid model

Logrank

Comparing survival curves of two groups using the log rank test

Comparing survival curves of two groups using the log rank test.Comparison of two survival curves can be done using a statistical hypothesis test called the log rank test. It is used to test the null

Raspberry Pi Board LED Test Utility

This is simple utility for Raspberry Pi board LED testing

Source Panel Method applied to Flow around Cylinder

Source Panel Method applied to Flow around Cylinder. Example 3.19 from Anderson's book

Source Panel Method applied to Flow around Cylinder. Example 3.19 from Anderson's "Fundamentals of Aerodynamics". Serves as a good primer to CFD.

COCHRAN Q TEST

Cochran's Q Test on dichotomous data for k-related samples

H = COCHRANQTEST(X) performs the non-parametric Cochran's Q-test on the hypothesis that the K columns of N-by-K matrix have the same number of successes and failures. H==0 indicates that the null

Chaos test

A test for chaotic dynamics of a noisy time series based on the Lyapunov exponent.

This test performs the test for chaotic dynamics of a noisy time series based on the Lyapunov exponent. The input is a vector of observed time series which can be stochastic or chaotic, usually time

Modified-MannKendall-Test

A modified version of the Mann-Kendall Test that works with autocorrelated data.

Modified-MannKendall-TestReleased on MATLAB FileExchangeTo get started refer the file demo.mUseThe modified Mann-Kendall test is a hypothesis test that determines whether a given sequence of data has

Cramer-von Mises test

Cramer-von Mises test for goodness-of-fit of a single sample

Cramer-von Mises test for goodness-of-fit of a single sample based on the exact and asymptotic distribution of Csörgo & Faraway (1996).

Mann-Kendall Test

Mann-Kendall non-parametric trend test.

The code performs original two tailed Mann-Kendall test. It tests the null hypothesis of trend absence in the vector V, against the alternative of trend. The result of the test is returned in H = 1

Generates test sample(audio)

Generates test samples by randomly combining a known set of test data.

This is utility function used to generate test samples by randomly combining audio samples (encoded in wave format) located at a specified directory*[out save_dir] =

Chi-square test - contingency tables

This function performs the chi-square test for 2x2 contingency tables

square test which is based on the chi square distribution. Thechi square test might become unreliable when the total number of expected frequencies(cell values in the contingency table) are not large

Stationarity test

The stationarity of a time series is evaluated by using the reverse arrangement test or moving-window functions

stationaryTestsMatlab functions to test the stationarity of a random processSummaryThe N-th order stationarity [1] of a random process is assessed using two tests. In the present submission, only the

Inhull

Efficient test for points inside a convex hull in n dimensions

Testing if a point is inside a convex hull can be done in a variety of ways. Inhull converts the problem into a dot product. If not supplied, it also computes the convex hull too. Inhull also