bootQuantile | R Documentation |
Begin with the output of bootPairs function, a (n999 by p-1) matrix when
there are p columns of data, bootQuantile
produces a (k by p-1) mtx
of quantile(s) of bootstrap ouput assuming that there are k quantiles needed.
bootQuantile(out, probs = c(0.025, 0.975), per100 = TRUE)
out |
output from bootPairs with p-1 columns and n999 rows |
probs |
quantile evaluation probabilities. The default is k=2, probs=c(.025,0.975) for a 95 percent confidence interval. Note that there are k=2 quantiles desired for each column with this specification |
per100 |
logical (default per100=TRUE) to change the range of 'sum' to [-100, 100] values which are easier to interpret |
CI k quantiles evaluated at probs as a matrix with k rows
and quantile of pairwise p-1 indexes representing p-1 column pairs
(fixing the first column in each pair)
This function summarizes the
output of of bootPairs(mtx)
(a n999 by p-1 matrix)
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. #'
Prof. H. D. Vinod, Economics Dept., Fordham University, NY
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")}
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 silentPairs
.
## Not run:
options(np.messages = FALSE)
set.seed(34);x=sample(1:10);y=sample(2:11)
bb=bootPairs(cbind(x,y),n999=29)
bootQuantile(bb) #gives summary stats for n999 bootstrap sum computations
bb=bootPairs(airquality,n999=999);options(np.messages=FALSE)
bootQuantile(bb,tau=0.476)#signs for n999 bootstrap sum computations
data('EuroCrime')
attach(EuroCrime)
bb=bootPairs(cbind(crim,off),n999=29) #col.1= crim causes off
#hence positive signs are more intuitively meaningful.
#note that n999=29 is too small for real problems, chosen for quickness here.
bootQuantile(bb)# quantile matrix for n999 bootstrap sum computations
## End(Not run)
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