evalPol: Evaluating Polynomials

In MonoPoly: Functions to Fit Monotone Polynomials

Description

Function to evaluate polynomials in a numerical robust way using the Horner scheme

Usage

evalPol(x, beta)

Arguments

x	numerical values at which to evaluate polynomials, can be provided in a vector, matrix, array or data frame
beta	numerical vector containing the coefficient of the polynomial

Value

The result of evaluating the polynomial at the values in x, returned in the same dimension as x has.

Author(s)

Berwin A Turlach <[e-mail]>

Examples

beta <- c(1,2,1)

x <- 0:10
evalPol(x, beta)
str(evalPol(x, beta))

x <- cbind(0:10, 10:0)
evalPol(x, beta)
str(evalPol(x, beta))


x <- data.frame(x=0:10, y=10:0)
evalPol(x, beta)
str(evalPol(x, beta))

Example output

Loading required package: quadprog
 [1]   1   4   9  16  25  36  49  64  81 100 121
 num [1:11] 1 4 9 16 25 36 49 64 81 100 ...
      [,1] [,2]
 [1,]    1  121
 [2,]    4  100
 [3,]    9   81
 [4,]   16   64
 [5,]   25   49
 [6,]   36   36
 [7,]   49   25
 [8,]   64   16
 [9,]   81    9
[10,]  100    4
[11,]  121    1
 num [1:11, 1:2] 1 4 9 16 25 36 49 64 81 100 ...
     x   y
1    1 121
2    4 100
3    9  81
4   16  64
5   25  49
6   36  36
7   49  25
8   64  16
9   81   9
10 100   4
11 121   1
'data.frame':	11 obs. of  2 variables:
 $ x: num  1 4 9 16 25 36 49 64 81 100 ...
 $ y: num  121 100 81 64 49 36 25 16 9 4 ...

MonoPoly documentation built on May 2, 2019, 7:59 a.m.