predict.nls
Predicting from Nonlinear Least Squares Fits

Description

Produces predicted values.

Usage

predict(object, newdata, se.fit = FALSE, scale = NULL, df = Inf, interval = c("none", "confidence", "prediction"), level = 0.95, ...) 

Arguments

object an object that inherites from class nls.
newdata a named list or a data frame, which is used to provide variables to predict. If this argument is not provided, or it is not a named list or data.frame, then the fitted values at the original data points are returned.
se.fit a logical flag. If TRUE, calculates the standard errors of the predictions. This argument is not used at present.
scale a number used as the residual standard deviation in calculating the standard errors. This argument is not used at present.
df a positive numer. Specifies the number of degrees of freedom for the scale estimate. This argument is not used at present.
interval a character string. Indicates whether to calculate prediction intervals or a confidence interval on the mean response. This argument is not used at present.
level a number between 0 to 1. Provides the confidence level for the intervals to be calcuated. This argument is not used at present.
... any other optional arguments. This argument is not used at present.

Details

predict.nls produces predicted values; use the evaluating the regression function in the frame newdata.
Value
returns a vector of predictions.
See Also
nls, predict
Examples
tDat <- data.frame(
    x = c(2.3, 3.2, 4.3, 5.3, 5.7, 6.3, 6.8, 9.6, 9.8, 10.7,
         12.7, 13.2, 13.4, 13.7, 14.5, 15.4, 16.5, 17, 17.1, 17.9),
    y = c(8.8, 9.6, 8, 4.2, 2.5, 0, -2, -7.1, -6.9, -4.9, 
         1.6, 2.8, 3.4, 3.8, 4.6, 4.1, 1.9, 0.7, 0.2, -1.8))
fit1 <- nls(y ~ beta1 * sin(x * freq1) + beta2 * sin(x * freq2),
    data=tDat, start=list(freq1=0.5, freq2=0.3, beta1=5, beta2=5))
# return fitted values on original data points
predict(fit1)
# predict from the first two fitted data points
identical(predict(fit1, newdata=list(x=c(2.3,3.2))), predict(fit1)[1:2])
# predict from a set of x values
predict(fit1, newdata=data.frame(x=seq(0,20,by=2)))
Package stats version 6.1.1-7
Package Index