bootPairs | R Documentation |

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.

```
bootPairs(mtx, ctrl = 0, n999 = 9)
```

`mtx` |
data matrix with two or more columns |

`ctrl` |
data matrix having control variable(s) if any |

`n999` |
Number of bootstrap replications (default=9) |

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.

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`

.

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")}

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 `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)
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)
```

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