Package 'testcorr' reference manual

Title:	Testing Zero Correlation
Description:	Computes the test statistics for examining the significance of autocorrelation in univariate time series, cross-correlation in bivariate time series, Pearson correlations in multivariate series and test statistics for i.i.d. property of univariate series given in Dalla, Giraitis and Phillips (2020), <https://cowles.yale.edu/sites/default/files/files/pub/d21/d2194-r.pdf>.
Authors:	Violetta Dalla, Liudas Giraitis and Peter C. B. Phillips
Maintainer:	Violetta Dalla <[email protected]>
License:	GPL-3
Version:	0.2.0
Built:	2025-02-20 03:59:38 UTC
Source:	https://github.com/cran/testcorr

Testing zero autocorrelation

Description

The function ac.test computes the test statistics for examining the null hypothesis of zero autocorrelation for univariate time series given in Dalla, Giraitis and Phillips (2020).

Usage

ac.test(x, max.lag, alpha = 0.05, lambda = 2.576, plot = TRUE,
        table = TRUE, var.name = NULL, scale.font = 1)
ac.test(x, max.lag, alpha = 0.05, lambda = 2.576, plot = TRUE,
        table = TRUE, var.name = NULL, scale.font = 1)

Arguments

`x`	A numeric vector or a univariate numeric time series object or a data frame.
`max.lag`	Maximum lag at which to calculate the test statistics.
`alpha`	Significance level for hypothesis testing used in the plots. Default is 0.05.
`lambda`	Threshold in $\widetilde{Q}$ test statistics. Default is 2.576.
`plot`	Logical. If TRUE the sample autocorrelations with their confidence bands and the cumulative statistics with their critical values are plotted. Default is TRUE.
`table`	Logical. If TRUE the sample autocorrelations, the confidence bands, the test statistics and their p-values are printed out. Default is TRUE.
`var.name`	NULL or a character string specifying the variable name. If NULL and x has name, the name of x is used. If NULL and x has no name, the string "x" is used. Default is NULL.
`scale.font`	A positive number indicating the scaling of the font size in the plots. Default is 1.

Details

The standard $t$ and robust $\widetilde{t}$ statistics are for testing the null hypothesis $H_0:\rho_k=0$ at lags $k=1,...,max.lag$ , and the standard $LB$ and robust $\widetilde{Q}$ statistics are for testing the null hypothesis $H_0:\rho_1=...=\rho_m=0$ at lags $m=1,...,max.lag$ , where $\rho_k$ denotes the autocorrelation of $x_t$ at lag $k$ .

Value

An object of class "ac.test", which is a list with the following components:

`lag`	The lags used.
`ac`	The sample autocorrelations.
`scb`	The lower and upper limit of the confidence bands based on the standard test statistics.
`rcb`	The lower and upper limit of the confidence bands based on the robust test statistics.
`t`	The $t$ test statistics.
`pvt`	The p-values for the $t$ test statistics.
`ttilde`	The $\widetilde{t}$ test statistics.
`pvttilde`	The p-values for the $\widetilde{t}$ test statistics.
`lb`	The $LB$ test statistics.
`pvlb`	The p-values for the $LB$ test statistics.
`qtilde`	The $\widetilde{Q}$ test statistics.
`pvqtilde`	The p-values for the $\widetilde{Q}$ test statistics.

Note

Missing values are not allowed.

Author(s)

Violetta Dalla, Liudas Giraitis and Peter C. B. Phillips

References

Dalla, V., Giraitis, L. and Phillips, P. C. B. (2020). "Robust Tests for White Noise and Cross-Correlation". Cowles Foundation, Discussion Paper No. 2194, https://cowles.yale.edu/sites/default/files/files/pub/d21/d2194-r.pdf.

Examples

x <- rnorm(100)
ac.test(x, max.lag = 10)
x <- rnorm(100)
ac.test(x, max.lag = 10)

Testing zero cross-correlation

Description

The function cc.test computes the test statistics for examining the null hypothesis of zero cross-correlation for bivariate time series given in Dalla, Giraitis and Phillips (2020).

Usage

cc.test(x, y, max.lag, alpha = 0.05, lambda = 2.576, plot = TRUE,
        table = TRUE, var.names = NULL, scale.font = 1)
cc.test(x, y, max.lag, alpha = 0.05, lambda = 2.576, plot = TRUE,
        table = TRUE, var.names = NULL, scale.font = 1)

Arguments

`x`	A numeric vector or a univariate numeric time series object or a data frame.
`y`	A numeric vector or a univariate numeric time series object or a data frame.
`max.lag`	Maximum lag at which to calculate the test statistics.
`alpha`	Significance level for hypothesis testing used in the plots. Default is 0.05.
`lambda`	Threshold in $\widetilde{Q}$ test statistics. Default is 2.576.
`plot`	Logical. If TRUE the sample cross-correlations with their confidence bands and the cumulative statistics with their critical values are plotted. Default is TRUE.
`table`	Logical. If TRUE the sample cross-correlations, the confidence bands, the test statistics and their p-values are printed out. Default is TRUE.
`var.names`	NULL or a character string specifying the variable names. If NULL and x,y have names, the names of x,y are used. If NULL and x,y have no names, the string c("x","y") is used. Default is NULL.
`scale.font`	A positive number indicating the scaling of the font size in the plots. Default is 1.

Details

The standard $t$ and robust $\widetilde{t}$ statistics are for testing the null hypothesis $H_0:\rho_k=0$ at lags $k=-max.lag,...,-1,0,1,max.lag$ , and the standard $HB$ and robust $\widetilde{Q}$ statistics are for testing the null hypothesis $H_0:\rho_0=...=\rho_m=0$ at lags $m=-max.lag,...,-1,0,1,max.lag$ , where $\rho_k$ denotes the cross-correlation of $x_t$ and $y_{t-k}$ at lag $k$ .

Value

An object of class "cc.test", which is a list with the following components:

`lag`	The lags used.
`cc`	The sample cross-correlations.
`scb`	The lower and upper limit of the confidence bands based on the standard test statistics.
`rcb`	The lower and upper limit of the confidence bands based on the robust test statistics.
`t`	The $t$ test statistics.
`pvt`	The p-values for the $t$ test statistics.
`ttilde`	The $\widetilde{t}$ test statistics.
`pvtttilde`	The p-values for the $\widetilde{t}$ test statistics.
`hb`	The $HB$ test statistics.
`pvhb`	The p-values for the $HB$ test statistics.
`qtilde`	The $\widetilde{Q}$ test statistics.
`pvqtilde`	The p-values for the $\widetilde{Q}$ test statistics.

Note

Missing values are not allowed.

Author(s)

Violetta Dalla, Liudas Giraitis and Peter C. B. Phillips

References

Examples

x <- rnorm(100)
y <- rnorm(100)
cc.test(x, y, max.lag = 10)
x <- rnorm(100)
y <- rnorm(100)
cc.test(x, y, max.lag = 10)

Testing iid property

Description

The function iid.test computes the test statistics for examining the null hypothesis of i.i.d. property for univariate series given in Dalla, Giraitis and Phillips (2020).

Usage

iid.test(x, max.lag, alpha = 0.05, plot = TRUE, table = TRUE,
         var.name = NULL, scale.font = 1)
iid.test(x, max.lag, alpha = 0.05, plot = TRUE, table = TRUE,
         var.name = NULL, scale.font = 1)

Arguments

`x`	A numeric vector or a univariate numeric time series object or a data frame.
`max.lag`	Maximum lag at which to calculate the test statistics.
`alpha`	Significance level for hypothesis testing used in the plots. Default is 0.05.
`plot`	Logical. If TRUE the test statistics and their critical values are plotted. Default is TRUE.
`table`	Logical. If TRUE the test statistics and their p-values are printed out. Default is TRUE.
`var.name`	NULL or a character string specifying the variable name. If NULL and x has name, the name of x is used. If NULL and x has no name, the string "x" is used. Default is NULL.
`scale.font`	A positive number indicating the scaling of the font size in the plots. Default is 1.

Details

The $J_{x,|x|}$ and $J_{x,x^2}$ statistics are for testing the null hypothesis of i.i.d. at lag $k$ , $k=1,...,max.lag$ , and the $C_{x,|x|}$ and $C_{x,x^2}$ statistics are for testing the null hypothesis of i.i.d. at lags $1,...,m$ , $m=1,...,max.lag$ .

Value

An object of class "iid.test", which is a list with the following components:

`lag`	The lags used.
`jab`	The $J_{x,\|x\|}$ test statistics.
`pvjab`	The p-values for the $J_{x,\|x\|}$ test statistics.
`jsq`	The $J_{x,x^2}$ test statistics.
`pvjsq`	The p-values for the $J_{x,x^2}$ test statistics.
`cab`	The $C_{x,\|x\|}$ test statistics.
`pvcab`	The p-values for the $C_{x,\|x\|}$ test statistics.
`csq`	The $C_{x,x^2}$ test statistics.
`pvcsq`	The p-values for the $C_{x,x^2}$ test statistics.

Note

Missing values are not allowed.

Author(s)

Violetta Dalla, Liudas Giraitis and Peter C. B. Phillips

References

Examples

x <- rnorm(100)
iid.test(x, max.lag = 10)
x <- rnorm(100)
iid.test(x, max.lag = 10)

Testing zero Pearson correlation

Description

The function rcorr.test computes the test statistics for examining the null hypothesis of zero Pearson correlation for multivariate series in Dalla, Giraitis and Phillips (2020).

Usage

rcorr.test(x, plot = TRUE, table = TRUE, var.names = NULL,
           scale.font = 1)
rcorr.test(x, plot = TRUE, table = TRUE, var.names = NULL,
           scale.font = 1)

Arguments

`x`	A numeric matrix or a multivariate numeric time series object or a data frame.
`plot`	Logical. If TRUE the sample Pearson correlations and the p-values for significance are plotted. Default is TRUE.
`table`	Logical. If TRUE the sample Pearson correlations and the p-values for significance are printed out. Default is TRUE.
`var.names`	NULL or a character string specifying the variable names. If NULL and x has names, the names of x are used. If NULL and x has no names, the string c("x[1]","x[2]",...) is used. Default is NULL.
`scale.font`	A positive number indicating the scaling of the font size in the plots. Default is 1.

Details

The p-value of the robust $\widetilde{t}$ statistic is for testing the null hypothesis $H_0:\rho_{i,j}=0$ , where $\rho_{i,j}$ denotes the correlation of $x_{i}$ and $x_{j}$ .

Value

An object of class "rcorr.test", which is a list with the following components:

`pc`	The sample Pearson correlations.
`pv`	The p-values for the $\widetilde{t}$ test statistics.

Note

Missing values are not allowed.

Author(s)

Violetta Dalla, Liudas Giraitis and Peter C. B. Phillips

References

Examples

x <- matrix(rnorm(400),100)
rcorr.test(x)
x <- matrix(rnorm(400),100)
rcorr.test(x)

Package 'testcorr'

Help Index

Testing zero autocorrelation

Description

Usage

Arguments

Details

Value

Note

Author(s)

References

Examples

Testing zero cross-correlation

Description

Usage

Arguments

Details

Value

Note

Author(s)

References

Examples

Testing iid property

Description

Usage

Arguments

Details

Value

Note

Author(s)

References

Examples

Testing zero Pearson correlation

Description

Usage

Arguments

Details

Value

Note

Author(s)

References

Examples