somePairs function

Function reporting kernel causality results as a 7-column matrix.(deprecated)

Function reporting kernel causality results as a 7-column matrix.(deprecated)

This function lets the user choose one of three criteria to determine causal direction by setting typ as 1, 2 or 3. This function reports results for only one criterion at a time unlike the function some0Pairs which summarizes the resulting causal directions for all criteria with suitable weights. If some variables are control' variables, use someCPairs`, C=control.

somePairs(mtx, dig = 6, verbo = FALSE, typ = 1, rnam = FALSE)

Arguments

  • mtx: The data matrix in the first column is paired with all others.
  • dig: Number of digits for reporting (default dig=6).
  • verbo: Make verbo= TRUE for printing detailed steps.
  • typ: Must be 1 (default), 2 or 3 for the three criteria.
  • rnam: Make rnam= TRUE if cleverly created rownames are desired.

Returns

A matrix containing causal identification results for one criterion. The first column of the input mtx having p columns is paired with (p-1) other columns The output matrix headings are self-explanatory and distinct for each criterion Cr1 to Cr3.

Details

(typ=1) reports ('Y', 'X', 'Cause', 'SD1apd', 'SD2apd', 'SD3apd', 'SD4apd') nameing variables identifying 'cause' and measures of stochastic dominance using absolute values of kernel regression gradients comparing regresson of X on Y with that of Y on X.

(typ=2)

reports ('Y', 'X', 'Cause', 'SD1res', 'SD2res', 'SD3res', 'SD4res') and measures of stochastic dominance using absolute values of kernel regression residuals comparing regresson of X on Y with that of Y on X.

(typ=3)

reports ('Y', 'X', 'Cause', 'rX|Y', 'rY|X', 'r', 'p-val') containing generalized correlation coefficients r*, 'r' refers to the Pearson correlation coefficient and p-val column has the p-values for testing the significance of Pearson's 'r'.

Examples

## Not run: data(mtcars) somePairs(mtcars) ## End(Not run)

References

H. D. Vinod 'Generalized Correlation and Kernel Causality with Applications in Development Economics' in Communications in Statistics -Simulation and Computation, 2015, tools:::Rd_expr_doi("10.1080/03610918.2015.1122048")

See Also

The related function some0Pairs may be more useful, since it reports on all three criteria (by choosing typ=1,2,3) and further summarizes their results by weighting to help choose causal paths.

Author(s)

Prof. H. D. Vinod, Economics Dept., Fordham University, NY

  • Maintainer: H. D. Vinod
  • License: GPL (>= 2)
  • Last published: 2023-10-09

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