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

Description Usage Arguments Value Note Author(s) References See Also Examples

View source: R/bootPairs.R

Description

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 approximate preponderance of a particular sign which determines the causal direction.

Usage

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bootPairs(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

out When mtx has p columns, out of bootPairs(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 silentPairs(mtx) applied to each bootstrap sample separately.

Note

This computation is computer intensive and generally very slow. It may be better to use it at a later stage in the investigation when 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, https://doi.org/gffn86

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

See Also

See Also silentPairs.

Examples

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

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

data('EuroCrime')
attach(EuroCrime)
bootPairs(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 Jan. 4, 2022, 1:08 a.m.