bootPair2 {generalCorr} | R Documentation |
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, 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)