# abs_stdresC: Absolute values of residuals of kernel regressions of x on y... In generalCorr: Generalized Correlations, Causal Paths and Portfolio Selection

 abs_stdresC R Documentation

## Absolute values of residuals of kernel regressions of x on y when both x and y are standardized and control variables are present (C for control presence).

### Description

1) standardize the data to force mean zero and variance unity, 2) kernel regress x on y and a matrix of control variables, with the option ‘residuals = TRUE’ and finally 3) compute the absolute values of residuals.

### Usage

``````abs_stdresC(x, y, ctrl)
``````

### Arguments

 `x` vector of data on the dependent variable `y` data on the regressors which can be a matrix `ctrl` Data matrix on the control variable(s) beyond causal path issues

### Details

The first argument is assumed to be the dependent variable. If `abs_stdres(x,y)` is used, you are regressing x on y (not the usual y on x). The regressors can be a matrix with two or more columns. The missing values are suitably ignored by the standardization.

### Value

Absolute values of kernel regression residuals are returned after standardizing the data on both sides so that the magnitudes of residuals are comparable between regression of x on y on the one hand and regression of y on x on the other.

### Author(s)

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

### References

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")}

See `abs_stdres`.

### Examples

``````
## Not run:
set.seed(330)
x=sample(20:50)
y=sample(20:50)
z=sample(21:51)
abs_stdresC(x,y,ctrl=z)

## End(Not run)

``````

generalCorr documentation built on Oct. 10, 2023, 1:06 a.m.