If there are p columns of data,
bootSignPcent produces a p-1 by 1 vector
of probabilities of correct signs assuming that the mean of n999 values
has the correct sign and assuming that m of the 'ui' index values inside the
range [-tau, tau] are neither positive nor negative but
indeterminate or ambiguous (being too close to zero). That is,
the denominator of P(+1) or P(-1) is (n999-m) if m signs are too close to zero.
Thus it measures the bootstrap success rate in identifying the correct sign, when the sign
of the average of n999 bootstraps is assumed to be correct.
bootSignPcent(out, tau = 5)
output from bootPairs with p-1 columns and n999 rows
threshold to determine what value is too close to zero, default tau=5 is 5 percent threshold for the unanimity index ui
mtx has p columns,
reports pairwise p-1 signs representing
(fixing the first column in each pair)
the average sign after averaging 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
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, https://doi.org/gffn86
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
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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) bootSignPcent(bb,tau=5) #gives success rate in n999 bootstrap sum computations bb=bootPairs(airquality,n999=999);options(np.messages=FALSE) bootSignPcent(bb,tau=5)#success rate for signs from n999 bootstraps data('EuroCrime');options(np.messages=FALSE) 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. bootSignPcent(bb,tau=5)#successful signs from n999 bootstraps ## End(Not run)
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