Description Usage Arguments Value Author(s) References Examples
Returns the numerical partial derivative of y
with respect to [wrt] any regressor for a point of interest. Finite difference method is used with NNS.reg estimates as f(x + h)
and f(x  h)
values.
1 
x 
a numeric matrix or data frame. 
y 
a numeric vector with compatible dimensions to 
wrt 
integer; Selects the regressor to differentiate with respect to (vectorized). 
eval.points 
numeric or options: ("obs", "apd", "mean", "median", "last"); Regressor points to be evaluated.

mixed 
logical; 
messages 
logical; 
Returns columnwise matrix of wrt regressors:
dy.d_(...)[, wrt]$First
the 1st derivative
dy.d_(...)[, wrt]$Second
the 2nd derivative
dy.d_(...)[, wrt]$Mixed
the mixed derivative (for two independent variables only).
Fred Viole, OVVO Financial Systems
Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" https://www.amazon.com/dp/1490523995/ref=cm_sw_su_dp
Vinod, H. and Viole, F. (2020) "Comparing Old and New Partial Derivative Estimates from Nonlinear Nonparametric Regressions" https://www.ssrn.com/abstract=3681104
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27  ## Not run:
set.seed(123) ; x_1 < runif(1000) ; x_2 < runif(1000) ; y < x_1 ^ 2 * x_2 ^ 2
B < cbind(x_1, x_2)
## To find derivatives of y wrt 1st regressor for specific points of both regressors
dy.d_(B, y, wrt = c(1, 2), eval.points = t(c(.5, .5)))
## To find average partial derivative of y wrt 1st regressor,
only supply 1 value in [eval.points], or a vector of [eval.points]:
dy.d_(B, y, wrt = 1, eval.points = .5)
dy.d_(B, y, wrt = 1, eval.points = fivenum(B[,1]))
## To find average partial derivative of y wrt 1st regressor,
for every observation of 1st regressor:
apd < dy.d_(B, y, wrt = 1, eval.points = "apd")
plot(B[,1], apd[,1]$First)
## 95% Confidence Interval to test if 0 is within
### Lower CI
LPM.VaR(.025, 0, apd[,1]$First)
### Upper CI
UPM.VaR(.025, 0, apd[,1]$First)
## End(Not run)

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