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 (2022), <https://www.cambridge.org/core/journals/econometric-theory/article/abs/robust-tests-for-white-noise-and-crosscorrelation/4D77C12C52433F4C6735E584C779403A>, <https://elischolar.library.yale.edu/cowles-discussion-paper-series/57/>.
Authors:	Violetta Dalla [aut, cre], Liudas Giraitis [aut], Peter C. B. Phillips [aut]
Maintainer:	Violetta Dalla <[email protected]>
License:	GPL-3
Version:	0.4.0
Built:	2026-05-20 09:55:08 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 (2022).

Usage

ac.test(x, max.lag, m0 = 1, alpha = 0.05, lambda = 2.576,
        plot = TRUE, var.name = NULL, scale.font = 1)
ac.test(x, max.lag, m0 = 1, alpha = 0.05, lambda = 2.576,
        plot = TRUE, var.name = NULL, scale.font = 1)

Arguments

x

A numeric vector or a univariate numeric time series (ts, xts, zoo) object or a data frame variable.

max.lag

Maximum lag at which to calculate the test statistics.

m0

Minimum lag at which to calculate the cumulative test statistics. Default is 1.

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, 1) the sample autocorrelations with their confidence bands are plotted and 2) the cumulative test statistics with their critical values are plotted. Default is TRUE. Can be a logical vector for each of the plots 1)-2).

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 $H_0:\rho_{m_0}=...=\rho_m=0$ at lags $m=m_0,...,max.lag$ , 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 of the sample autocorrelations.

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.

lagc

The lags of the cumulative 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.

alpha

Significance level for hypothesis testing used in the plots.

varname

The variable name used in the plots/table.

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. (2022). "Robust Tests for White Noise and Cross-Correlation". Econometric Theory, 38(5), 913-941, doi:10.1017/S0266466620000341. Cowles Foundation, Discussion Paper No. 2194RS, https://elischolar.library.yale.edu/cowles-discussion-paper-series/57/.
Giraitis, L., Li, Y. and Phillips, P. C. B. (2024). "Robust Inference on Correlation under General Heterogeneity". Journal of Econometrics, 244(1), 105691, doi:10.1016/j.jeconom.2024.105691.

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 (2022).

Usage

cc.test(x, y, max.lag, m0 = 0, alpha = 0.05, lambda = 2.576,
        plot = TRUE, var.names = NULL, scale.font = 1)
cc.test(x, y, max.lag, m0 = 0, alpha = 0.05, lambda = 2.576,
        plot = TRUE, var.names = NULL, scale.font = 1)

Arguments

x

A numeric vector or a univariate numeric time series (ts, xts, zoo) object or a data frame variable.

y

A numeric vector or a univariate numeric time series (ts, xts, zoo) object or a data frame variable.

max.lag

Maximum lag at which to calculate the test statistics.

m0

Minimum lag at which to calculate the cumulative test statistics. Default is 0.

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, 1) the sample cross-correlations with their confidence bands are plotted and 2) the cumulative test statistics with their critical values are plotted. Default is TRUE. Can be a logical vector for each of the plots 1)-2).

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 $H_0:\rho_{m_0}=...=\rho_m=0$ 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 of the sample cross-correlations.

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.

lagc

The lags of the cumulative 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.

alpha

Significance level for hypothesis testing used in the plots.

varnames

The variable names used in the plots/table.

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 (2022).

Usage

iid.test(x, max.lag, m0 = 1, alpha = 0.05,
         plot = TRUE, var.name = NULL, scale.font = 1)
iid.test(x, max.lag, m0 = 1, alpha = 0.05,
         plot = TRUE, var.name = NULL, scale.font = 1)

Arguments

x

A numeric vector or a univariate numeric time series (ts, xts, zoo) object or a data frame variable.

max.lag

Maximum lag at which to calculate the test statistics.

m0

Minimum lag at which to calculate the cumulative test statistics. Default is 1.

alpha

Significance level for hypothesis testing used in the plots. Default is 0.05.

plot

Logical. If TRUE, 1) the test statistics (J) and their critical values are plotted and 2) the cumulative test statistics (C) with their critical values are plotted. Default is TRUE. Can be a logical vector for each of the plots 1)-2).

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 $m_0,...,m$ , $m=m_0,...,max.lag$ .

Value

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

lag

The lags of the test statistics.

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.

lagc

The lags of the cumulative 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.

alpha

Significance level for hypothesis testing used in the plots.

varname

The variable name used in the plots/table.

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 (2022).

Usage

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

Arguments

x

A numeric matrix or a multivariate numeric time series object (ts, xts, zoo) or a data frame.

plot

Logical. If TRUE the sample Pearson correlations and the p-values for significance are plotted. 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.

varnames

The variable names used in the plot/table.

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