• 2021-04-20 07:44:07

Two-sample F-test for equal variances

Syntax

H = vartest2(X,Y)

H = vartest2(X,Y,alpha)

H = vartest2(X,Y,alpha,tail)

[H,P] = vartest2(...)

[H,P,CI] = vartest2(...)

[H,P,CI,STATS] = vartest2(...)

[...] = vartest2(X,Y,alpha,tail,dim)

Description

H = vartest2(X,Y) performs an F test of the hypothesis that two independent samples, in the vectors X and Y, come from normal distributions with the same variance, against the alternative that they come from normal distributions with different variances. The result is H = 0 if the null hypothesis (variances are equal) cannot be rejected at the 5% significance level, or H = 1 if the null hypothesis can be rejected at the 5% level. X and Y can have different lengths. X and Y can also be matrices or n-dimensional arrays.

For matrices, vartest2 performs separate tests along each column, and returns a vector of results. X and Y must have the same number of columns. For n-dimensional arrays, vartest2 works along the first nonsingleton dimension. X and Y must have the same size along all the remaining dimensions.

H = vartest2(X,Y,alpha) performs the test at the significance level (100*alpha)%. alpha must be a scalar.

H = vartest2(X,Y,alpha,tail) performs the test against the alternative hypothesis specified by tail, where tail is one of the following single strings:

'both' — Variance is not Y (two-tailed test). This is the default.

'right' — Variance is greater than Y (right-tailed test).

'left' — Variance is less than Y (left-tailed test).

[H,P] = vartest2(...) returns the p-value, i.e., the probability of observing the given result, or one more extreme, by chance if the null hypothesis is true. Small values of P cast doubt on the validity of the null hypothesis.

[H,P,CI] = vartest2(...) returns a 100*(1-alpha)% confidence interval for the true variance ratio var(X)/var(Y).

[H,P,CI,STATS] = vartest2(...) returns a structure with the following fields:

'fstat' — Value of the test statistic

'df1' — Numerator degrees of freedom of the test

'df2' — Denominator degrees of freedom of the test

[...] = vartest2(X,Y,alpha,tail,dim) works along dimension dim of X. To pass in the default values for alpha or tail use [].

Example

Is the variance significantly different for two model years, and what is a confidence interval for the ratio of these variances?

[H,P,CI] = vartest2(MPG(Model_Year==82),MPG(Model_Year==76))

更多相关内容
• matlab开发-FTest。测试是否有必要通过改进数据错误来增加模型参数。
• 匿名用户1级2016-05-01 回答The following explaination may help U:Two-sample F-test for equal variancesSyntaxH = vartest2(X,Y)H = vartest2(X,Y,alpha)H = vartest2(X,Y,alpha,tail)[H,P] = vartest2(...)[H,P...

匿名用户

1级

2016-05-01 回答

The following explaination may help U:

Two-sample F-test for equal variances

Syntax

H = vartest2(X,Y)

H = vartest2(X,Y,alpha)

H = vartest2(X,Y,alpha,tail)

[H,P] = vartest2(...)

[H,P,CI] = vartest2(...)

[H,P,CI,STATS] = vartest2(...)

[...] = vartest2(X,Y,alpha,tail,dim)

Description

H = vartest2(X,Y) performs an F test of the hypothesis that two independent samples, in the vectors X and Y, come from normal distributions with the same variance, against the alternative that they come from normal distributions with different variances. The result is H = 0 if the null hypothesis (variances are equal) cannot be rejected at the 5% significance level, or H = 1 if the null hypothesis can be rejected at the 5% level. X and Y can have different lengths. X and Y can also be matrices or n-dimensional arrays.

For matrices, vartest2 performs separate tests along each column, and returns a vector of results. X and Y must have the same number of columns. For n-dimensional arrays, vartest2 works along the first nonsingleton dimension. X and Y must have the same size along all the remaining dimensions.

H = vartest2(X,Y,alpha) performs the test at the significance level (100*alpha)%. alpha must be a scalar.

H = vartest2(X,Y,alpha,tail) performs the test against the alternative hypothesis specified by tail, where tail is one of the following single strings:

'both' — Variance is not Y (two-tailed test). This is the default.

'right' — Variance is greater than Y (right-tailed test).

'left' — Variance is less than Y (left-tailed test).

[H,P] = vartest2(...) returns the p-value, i.e., the probability of observing the given result, or one more extreme, by chance if the null hypothesis is true. Small values of P cast doubt on the validity of the null hypothesis.

[H,P,CI] = vartest2(...) returns a 100*(1-alpha)% confidence interval for the true variance ratio var(X)/var(Y).

[H,P,CI,STATS] = vartest2(...) returns a structure with the following fields:

'fstat' — Value of the test statistic

'df1' — Numerator degrees of freedom of the test

'df2' — Denominator degrees of freedom of the test

[...] = vartest2(X,Y,alpha,tail,dim) works along dimension dim of X. To pass in the default values for alpha or tail use [].

Example

Is the variance significantly different for two model years, and what is a confidence interval for the ratio of these variances?

[H,P,CI] = vartest2(MPG(Model_Year==82),MPG(Model_Year==76))

展开全文
• ## F检验matlab

千次阅读 2020-04-15 21:37:31
• matlab进行F检验2014-02-28 07:12阅读： Kevin3981像梦一样自由，像大地一样宽容关注Two-sample F-test for equal variancesSyntaxH = vartest2(X,Y)H = vartest2(X,Y,alpha)H = vartest2(X,Y,alpha,tail)[H,P] = ...

matlab进行F检验

2014-02-28 07:12阅读：

Kevin3981

像梦一样自由，像大地一样宽容

关注

Two-sample F-test for equal variances

Syntax

H = vartest2(X,Y)

H = vartest2(X,Y,alpha)

H = vartest2(X,Y,alpha,tail)

[H,P] = vartest2(...)

[H,P,CI] = vartest2(...)

[H,P,CI,STATS] = vartest2(...)

[...] = vartest2(X,Y,alpha,tail,dim)

Description

H = vartest2(X,Y) performs an F test of the hypothesis that two

independent samples, in the vectors X and Y, come from normal distributions

with the same variance, against the alternative that they come from

normal distributions with different vari

ances. The result is H = 0 if the null hypothesis (variances are

equal) cannot be rejected at the 5% significance level, or H = 1 if

the null hypothesis can be rejected at the 5% level. X and Y can

have different lengths. X and Y can also be matrices or n-dimensional arrays.

For matrices, vartest2 performs separate tests along each column,

and returns a vector of results. X and Y must have the same

number of columns. For n-dimensional arrays, vartest2 works along the

first nonsingleton dimension. X and Y must have the same size

along all the remaining dimensions.

H = vartest2(X,Y,alpha) performs the test at the significance level

(100*alpha)%. alpha must be a scalar.

H = vartest2(X,Y,alpha,tail) performs the test against the

alternative hypothesis specified by tail, where tail is one of the

following single strings:

'both' — Variance is not Y (two-tailed test). This is the

default.

'right' — Variance is greater than Y (right-tailed test).

'left' — Variance is less than Y (left-tailed test).

[H,P] = vartest2(...) returns the p-value, i.e., the probability of observing the

given result, or one more extreme, by chance if the null hypothesis

is true. Small values of P cast doubt on the validity of the null

hypothesis.

[H,P,CI] = vartest2(...) returns a 100*(1-alpha)% confidence

interval for the true variance ratio var(X)/var(Y).

[H,P,CI,STATS] = vartest2(...) returns a structure with the

following fields:

'fstat' — Value of the test statistic

'df1' — Numerator degrees of freedom of the test

'df2' — Denominator degrees of freedom of the test

[...] = vartest2(X,Y,alpha,tail,dim) works along dimension dim of

X. To pass in the default values for alpha or tail use [].

Example

Is the variance significantly different for two model years, and

what is a confidence interval for the ratio of these

variances?

[H,P,CI] = vartest2(MPG(Model_Year==82),MPG(Model_Year==76))

展开全文
• 昨天做论文，用了数学建模，公式是生产道格拉斯生产函数，统计软件Matlab7.0 怎么都安装不了。...1,T检验和F检验的由来一般而言，为了确定从样本(sample)统计结果推论至总体时所犯错的概率，我们会利用...
• F检验(F-test)，最常用的别名叫做联合假设检验(英语：joint hypotheses test)，它是一种在零假设(null hypothesis, H0)之下，统计值服从F-分布的检验。常用于方差分析、方差齐次检验，对于数据的正态性比较敏感，...
• 在输入框录入用空格、制表符、回车符或(英文半角)逗号隔开的数据序列(1)和数据序列(2)。点击计算按钮，本计算软件将快速求出输入序列元素的...F检验(F-test)，最常用的别名叫做联合假设检验(英语：joint hypotheses...
• matlab精度检验代码f2matlab f2matlab.m的自述文件 目录：-1。 支持f2matlab和咨询0。免责声明 客观的 动机 错误报告和愿望清单 F2MATLAB功能 F2MATLAB的局限性 如何使用F2MATLAB 例子 修订记录 -1。支持f2matlab。 ...
• matlab精度检验代码F-Clip —完全卷积线解析 该存储库包含该论文的官方PyTorch实现：*，，，。 *。 介绍 我们的方法（F-Clip）是一种简单有效的神经网络，用于从给定的图像和视频中检测线路。 它在准确性和速度上都...
• MatLab 函数 FRIEDMAN 仅使用卡方近似值。 相反，MYFRIEDMAN对小样本使用精确分布，对大样本使用卡方和F分布。 如果 p 值显着，则进行事后多重比较。 由朱塞佩卡迪罗创建giuseppe.cardillo-edta
• 基于matlab假设w检验代码该文件夹包含一些文件，这些文件使用Python中的数值模拟来探索数据科学中的基本概念。 这包括诸如中心极限定理，t分布，F分布，置信区间，p值，假设检验和线性回归等主题。 Jupyter笔记本最...
• matlab精度检验代码validspike：MATLAB中的峰值排序和验证工具 这是用于对细胞外多通道神经元记录进行峰值分类，计算验证指标并生成合成数据集的软件包。 Alex Barnett和Jeremy Magland，2014年11月至2015年8月，...
• 非参数方差分析的 Kruskal-Wallis 检验在统计学中，Kruskal-Wallis 按等级对方差进行单向分析（命名为（威廉·克鲁斯卡尔（William Kruskal）和W.艾伦·沃利斯（W.Allen Wallis） 检验各组... 此函数还计算 F、Beta 和
• matlab精度检验代码将Slicer DB导出为nifti vglrun /opt/apps/slicer/Slicer-4.10.2-linux-amd64/Slicer --no-main-window --python-script ./anonymize.py Matlab的例子 用法 将dicome转换为nifti并匿名化数据 使...
• 跟随Anderson（doi：10.1139 / cjfas-58-3-626）使用分组变量上的数据置换估算单向方差分析的P值。
• matlab精度检验代码相互信息最大化，有效阅读唇语 介绍 纸的代码和模型。 此存储库的某些代码基于＆实现，并感谢他们的启发性工作。 依存关系 python 3.5 pytorch 1.0.0 OpenCVPython的4.1 数据集 LRW 用所提出的...
• 一元线性回归的matlab实现(含检验)【更新】说明：正文中命令部分可以直接在Matlab中运行，作者(Yangfd09_LZU)在MATLAB R2009a(7.8.0.347)中运行通过%求一元线性回归方程%数据要求：两行。第一行存放x的观察值，第二...
• Levene's F 检验用于检验多个样本对应的多个总体方差相等的原假设。 在分析之前，数据正在转换为平均值的绝对偏差。 然后执行单向方差分析。
• matlab精度检验代码版权声明：这些代码仅可用于复制提交给《国际电力与能源系统杂志》的未发表的论文“缺少数据的电力系统的时空自适应暂态稳定性评估”，并且不允许其他用途！ 缺少数据的电源系统的时空自适应暂态...
• matlab精度检验代码用于新颖性检测的内核PCA [] 介绍 异常（异常值或新颖性）检测方法的目标是在数据集中检测以常规背景点为主的异常点。 从定义上讲，异常是罕见的，并且通常是由不同的基础过程产生的[，]。 异常...
• matlab精度检验代码ARNT beta 1.1 arnt.m和RNewton.m中的算法被修改为更稳定，尤其是在需要高精度的情况下。 ARNT beta 1.0 用于解决流形上的优化问题的MATLAB软件。 问题与解决方案 该软件包包含有关流形上的优化...
• matlab精度检验代码pca_nl_test 主成分分析的非线性检验 **开发了附加的MATLAB代码，以测试记录数据中的基础结构是线性还是非线性。 Kruger等人（2005）引入的非线性度量通过将数据序列划分为较小的区域，计算丢弃的...
• Excel回归分析中的F检验这个F值不是用来检验R平方的。看图，不明白再来问我。excel的f检验双样本方差分析数据是有什么用excel的f检验本方差分析数据用于对两个正态总体方差进行。以便分析用了超过一个参数的统计，...
• 显著性检测FT的matlab实现，测试可用。包括FT.m ，论文。
• 一元线性回归的matlab实现含R方和F分布检验.pdf一元线性回归的matlab实现含R方和F分布检验.pdf一元线性回归的matlab实现含R方和F分布检验.pdf一元线性回归的matlab实现含R方和F分布检验.pdf一元线性回归的matlab实现...
• 一元线性回归的matlab实现含R方和F分布检验.docx一元线性回归的matlab实现含R方和F分布检验.docx一元线性回归的matlab实现含R方和F分布检验.docx一元线性回归的matlab实现含R方和F分布检验.docx一元线性回归的matlab...
• 一元线性回归的matlab实现含R方和F分布检验.doc.pdf一元线性回归的matlab实现含R方和F分布检验.doc.pdf一元线性回归的matlab实现含R方和F分布检验.doc.pdf一元线性回归的matlab实现含R方和F分布检验.doc.pdf一元线性...
• 一元线性回归的matlab实现含R方和F分布检验.doc.docx一元线性回归的matlab实现含R方和F分布检验.doc.docx一元线性回归的matlab实现含R方和F分布检验.doc.docx一元线性回归的matlab实现含R方和F分布检验.doc.docx一元...

...