bartels.test
(Package: lawstat) :
Ranked Version of von Neumann's Ratio Test for Randomness
This function performs the Bartels test for randomness which is based on the ranked version of von Neumann's ratio (RVN). Users can choose whether to test against two-sided, negative or positive correlation. NAs from the data are omitted.
● Data Source:
CranContrib
● Keywords: distribution, htest
● Alias: bartels.test
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neuhauser.hothorn.test
(Package: lawstat) :
Neuhauser-Hothorn double contrast test for a monotonic trend in variances
The function performs a test for a monotonic trend in variances. The test statistic suggested by Neuhauser and Hothorn (2000) is based on the classical Levene procedure (using the group means), the modified Brown-Forsythe Levene-type procedure (using the group medians) or the modified Levene-type procedure (using the group trimmed means). More robust versions of the test using the correction factor or structural zero removal method are also available. Two options for calculating critical values, namely, approximated and bootstrapped, are available. By default, NAs from the data are omitted. This function requires the mvtnorm package.
● Data Source:
CranContrib
● Keywords: htest
● Alias: neuhauser.hothorn.test
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j.maad
(Package: lawstat) :
MAAD estimated Robust Standard Deviation
This function computes the average absolute deviation from the sample median, which is a consistent robust estimate of the population standard deviation for normality distribution data. NAs from the data are omitted.
● Data Source:
CranContrib
● Keywords: distribution
● Alias: j.maad
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cmh.test
(Package: lawstat) :
The Cochran-Mantel-Haenszel Chi-square Test
This function performs the Cochran-Mantel-Haenszel (CMH) procedure. The CMH procedure tests homogeneity of population proportions after taking into account other factors. This procedure is widely used in various law cases, in particular, on equal employment and discrimination, as well in biological and phamaceutical studies.
● Data Source:
CranContrib
● Keywords: htest
● Alias: cmh.test
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brunner.munzel.test
(Package: lawstat) :
The Brunner-Munzel Test for Stochastic Equality
This function performs the Brunner-Munzel test for stochastic equality of two samples, which is also known as the Generalized Wilcoxon Test. NAs from the data are omitted.
● Data Source:
CranContrib
● Keywords: htest, nonparametric
● Alias: brunner.munzel.test
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rjb.test
(Package: lawstat) :
Test of Normailty - Robust Jarque Bera Test
This function performs the robust and classical Jarque-Bera tests of normality.
● Data Source:
CranContrib
● Keywords: htest
● Alias: rjb.test
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robust.mmm.test
(Package: lawstat) :
Robust Mudholkar-McDermott-Mudholkar test for ordered variances
The function performs a test for a monotonic trend in variances. The test statistic is based on a combination of the finite intersection approach and the two-sample t-test using Miller's transformation. By default, NAs are omitted.
● Data Source:
CranContrib
● Keywords: htest
● Alias: robust.mmm.test
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sj.test
(Package: lawstat) :
Test of Normality - SJ Test
This function performs the robust directed test of normality which is based on the ratio of the classical standard deviation s to the robust standard deviation J (Average Absolute Deviation from the Median (MAAD)) of the sample data.
● Data Source:
CranContrib
● Keywords: htest, ts
● Alias: sj.test
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This function plots the Lorenz curve that is a graphical representation of the cumulative distribution function. A user can choose for the Lorenz curve with single (default) or multiple weighting of data, for example, taking into account for single or multiple legislature representatives.
● Data Source:
CranContrib
● Keywords: dplot
● Alias: lorenz.curve
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lnested.test
(Package: lawstat) :
Test for a monotonic trend in variances
The function performs a test for a monotonic trend in variances. The test statistic is based on a combination of the finite intersection approach and the classical Levene procedure (using the group means), the modified Brown-Forsythe Levene-type procedure (using the group medians) or the modified Levene-type procedure (using the group trimmed means). More robust versions of the test using the correction factor or structural zero removal method are also available. Two options for calculating critical values, namely, approximated and bootstrapped, are available. By default, NAs from the data are omitted.
● Data Source:
CranContrib
● Keywords: htest
● Alias: lnested.test
●
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