ladfit: Fitting LAD Models

In LadR: Routines for Fit, Inference and Diagnostics in LAD Models

Description

Fitting LAD Models

Usage

ladfit(x, y, intercept = TRUE)

Arguments

x	A matrix or vector with explanatory variables.
y	A vector with response variables.
intercept	TRUE for a model with intercept and FALSE for a model without intercept.

Details

The Barrodale-Roberts algorithm, which is a specialized linear programming algorithm, is used.

Value

list defining the regression (compare with function lsfit).

coefficients	vector of coefficients.
residuals	residuals from the fit.
message	vector of one or two character strings stating whether a non-unique solution is possible, or if the x matrix was found to be rank deficient.

References

Barrodale, I., and Roberts, F.D.K. (1973). An improved algorithm for discrete L1 linear approximations. SIAM Journal of Numerical Analysis 10, 839-848.

Barrodale, I., and Roberts, F.D.K. (1974). Solution of an overdetermined system of equations in the L1 norm. Communications of the ACM 17, 319-320.

Bloomfield, P., and Steiger, W.L. (1983). Least Absolute Deviations: Theory, Applications, and Algorithms. Birkhauser, Boston, Mass.

Examples

### Using stackloss data

ladfit(stack.x, stack.loss, intercept =TRUE)

Example output

$coefficients
   Intercept     Air.Flow   Water.Temp   Acid.Conc. 
-39.68985367   0.83188403   0.57391310  -0.06086957 

$minimum
[1] 42.08116

$fitted.values
 [1] 36.939131 37.000000 31.571015 20.365218 19.217392 19.791305 20.000001
 [8] 20.000001 16.463769 14.020290 13.472464 12.959421 13.898551 13.802899
[15]  6.817392  7.000001  8.426088  8.000001  8.513044 13.382609 24.481160

$residuals
 [1]  5.0608706  0.0000000  5.4289861  7.6347828 -1.2173911 -1.7913042
 [7] -1.0000000  0.0000000 -1.4637681 -0.0202896  0.5275363  0.0405799
[13] -2.8985507 -1.8028984  1.1826082  0.0000000 -0.4260873  0.0000000
[19]  0.4869561  1.6173913 -9.4811592

$rank
[1] 4

$numIter
[1] 7

$info
[1] 1

LadR documentation built on May 1, 2019, 7:12 p.m.