T_alpha: Pseudorandom numbers from Asymptotic Null Distribution of...
In skedastic: Handling Heteroskedasticity in the Linear Regression Model
T_alpha R Documentation
Pseudorandom numbers from Asymptotic Null Distribution of Test Statistic for
Method of \insertCiteRackauskas07;textualskedastic
Description
A matrix of 2 ^ 14 rows and 16 columns. Each column contains
2 ^ 14 Monte Carlo replicates from the distribution of
T_{α} for a particular value of α, α=i/32,
i=0,1,…,15. The values were generated by first generating a
Brownian Bridge using m = 2 ^ 17 standard normal variates and then
applying Equation (11) from \insertCiteRackauskas07;textualskedastic.
It can be used to compute empirical approximate p-values for
implementation of the Rackauskas-Zuokas Test for heteroskedasticity. This
is a time-saving measure because, while rackauskas_zuokas
contains an option for simulating the p-value directly, this would be
computationally intensive for the authors' recommended m of
2 ^ 17. Passing the argument pvalmethod = "data" to
rackauskas_zuokas instructs the function to use the
pre-generated values in this data set to compute the empirical approximate
p-value for the test.
Usage
T_alpha
Format
An object of class matrix (inherits from array) with 16384 rows and 16 columns.
skedastic documentation built on Nov. 10, 2022, 5:43 p.m.
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| T_alpha | R Documentation |
Pseudorandom numbers from Asymptotic Null Distribution of Test Statistic for Method of \insertCiteRackauskas07;textualskedastic
Description
A matrix of 2 ^ 14 rows and 16 columns. Each column contains
2 ^ 14 Monte Carlo replicates from the distribution of
T_{α} for a particular value of α, α=i/32,
i=0,1,…,15. The values were generated by first generating a
Brownian Bridge using m = 2 ^ 17 standard normal variates and then
applying Equation (11) from \insertCiteRackauskas07;textualskedastic.
It can be used to compute empirical approximate p-values for
implementation of the Rackauskas-Zuokas Test for heteroskedasticity. This
is a time-saving measure because, while rackauskas_zuokas
contains an option for simulating the p-value directly, this would be
computationally intensive for the authors' recommended m of
2 ^ 17. Passing the argument pvalmethod = "data" to
rackauskas_zuokas instructs the function to use the
pre-generated values in this data set to compute the empirical approximate
p-value for the test.
Usage
T_alpha
Format
An object of class matrix (inherits from array) with 16384 rows and 16 columns.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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