reportRank {practicalSigni}

Function to report ranks of 13 criteria for practical significance

Description

This function generates a report based on the regression of y on bigx. It acknowledges that some methods for evaluating the importance of regressor in explaining y may give the importance value with a wrong (unrealistic) sign. For example, m2 reports t-values. Imagine that due to collinearity m2 value is negative when the correct sign from prior knowledge of the subject matter is that the coefficient should be positive, and hence the t-stat should be positive. The wrong sign means the importance of regressor in explaining y should be regarded as relatively less important. The larger the absolute size of the t-stat, the less its true importance in measuring y. The ranking of coefficients computed here suitably deprecates the importance of the regressor when its coefficient has the wrong sign (perverse direction).

Usage

reportRank(
  y,
  bigx,
  yesLatex = 1,
  yes13 = rep(1, 13),
  bsign = 0,
  dig = 3,
  verbo = FALSE
)

Arguments

y

A (T x 1) vector of dependent variable data y

bigx

a (T x p) data marix of xi regressor variables associated with the regression

yesLatex

default 1 means print Latex-ready Tables

yes13

default vector of ones to compute all 13 measures.

bsign

A (p x 1) vector of right signs of regression coefficients. Default is bsign=0 means the right sign is the same as the sign of the covariance, cov(y, xi)

dig

digits to be printed in latex tables, default, dig=d33

verbo

logical to print results by pracSig13, default=FALSE

Value

v15

practical significance index values (sign adjusted) for m1 to m5 using older linear and /or bivariate methods

v613

practical significance index values for m6 to m13 newer comprehensive and nonlinear methods

r15

ranks and average rank for m1 to m5 using older linear and /or bivariate methods

r613

ranks and average rank for m6 to m13 newer comprehensive and nonlinear methods

Note

The machine learning methods are subject to random seeds. For some seed values, m10 values from NNS.boost() rarely become degenerate and are reported as NA or missing. In that case the average ranking output r613 here needs adjustment.

Author(s)

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

See Also

pracSig13

Examples

set.seed(9)
y=sample(1:15,replace = TRUE)
x0=sample(2:16, replace = TRUE)
x2=sample(3:17, replace = TRUE)
x3=sample(4:18,replace = TRUE)
options(np.messages=FALSE)
yes13=rep(1,13)
yes13[10]=0
reportRank(y,bigx=cbind(x0,x2,x3),yes13=yes13)