bootPair2: Compute matrix of n999 rows and p-1 columns of bootstrap...

In generalCorr: Generalized Correlations, Causal Paths and Portfolio Selection

Compute matrix of n999 rows and p-1 columns of bootstrap ‘sum’ (scores from Cr1 to Cr3).

Description

The ‘2’ in the name of the function suggests a second implementation of ‘bootPair,’ where exact stochastic dominance, decileVote, and momentVote are used. Maximum entropy bootstrap (meboot) package is used for statistical inference using the sum of three signs sg1 to sg3, from the three criteria Cr1 to Cr3, to assess preponderance of evidence in favor of a sign, (+1, 0, -1). The bootstrap output can be analyzed to assess the approximate preponderance of a particular sign which determines the causal direction.

Usage

bootPair2(mtx, ctrl = 0, n999 = 9)

Arguments

mtx	data matrix with two or more columns
ctrl	data matrix having control variable(s) if any
n999	Number of bootstrap replications (default=9)

Value

Function creates a matrix called ‘out’. If the input to the function called mtx has p columns, the output out of bootPair2(mtx) is a matrix of n999 rows and p-1 columns, each containing resampled ‘sum’ values summarizing the weighted sums associated with all three criteria from the function silentPair2(mtx) applied to each bootstrap sample separately.

Note

This computation is computer-intensive and generally very slow. It may be better to use it later in the investigation, after a preliminary causal determination is already made. A positive sign for j-th weighted sum reported in the column ‘sum’ means that the first variable listed in the argument matrix mtx is the ‘kernel cause’ of the variable in the (j+1)-th column of mtx.

Author(s)

Prof. H. D. Vinod, Economics Dept., Fordham University, NY

References

Vinod, H. D. 'Generalized Correlation and Kernel Causality with Applications in Development Economics' in Communications in Statistics -Simulation and Computation, 2015, \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1080/03610918.2015.1122048")}

Zheng, S., Shi, N.-Z., and Zhang, Z. (2012). Generalized measures of correlation for asymmetry, nonlinearity, and beyond. Journal of the American Statistical Association, vol. 107, pp. 1239-1252.

Vinod, H. D. and Lopez-de-Lacalle, J. (2009). 'Maximum entropy bootstrap for time series: The meboot R package.' Journal of Statistical Software, Vol. 29(5), pp. 1-19.

Vinod, H. D. Causal Paths and Exogeneity Tests in Generalcorr Package for Air Pollution and Monetary Policy (June 6, 2017). Available at SSRN: https://www.ssrn.com/abstract=2982128

Vinod, Hrishikesh D., R Package GeneralCorr Functions for Portfolio Choice (November 11, 2021). Available at SSRN: https://ssrn.com/abstract=3961683

Vinod, Hrishikesh D., Stochastic Dominance Without Tears (January 26, 2021). Available at SSRN: https://ssrn.com/abstract=3773309

See Also

See Also silentPair2.

Examples

## Not run: 
options(np.messages = FALSE)
set.seed(34);x=sample(1:10);y=sample(2:11)
bb=bootPair2(cbind(x,y),n999=29)
apply(bb,2,summary) #gives summary stats for n999 bootstrap sum computations

bb=bootPair2(airquality,n999=999);options(np.messages=FALSE)
apply(bb,2,summary) #gives summary stats for n999 bootstrap sum computations

data('EuroCrime')
attach(EuroCrime)
bootPair2(cbind(crim,off),n999=29)#First col. crim causes officer deployment,
#hence positives signs are most sensible for such call to bootPairs
#note that n999=29 is too small for real problems, chosen for quickness here.

## End(Not run)

generalCorr documentation built on Oct. 10, 2023, 1:06 a.m.