probSign | R Documentation |
If there are p columns of data, probSign
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 'sum' 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.
probSign(out, tau = 0.476)
out |
output from bootPairs with p-1 columns and n999 rows |
tau |
threshold to determine what value is too close to zero, default tau=0.476 is equivalent to 15 percent threshold for the unanimity index ui |
sgn When mtx
has p columns, sgn
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
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)
probSign(bb,tau=0.476) #gives summary stats for n999 bootstrap sum computations
bb=bootPairs(airquality,n999=999);options(np.messages=FALSE)
probSign(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.
probSign(bb,tau=0.476)#signs for n999 bootstrap sum computations
## End(Not run)
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