predict.cusp: Predict method for Cusp Model Fits

In cusp: Cusp-Catastrophe Model Fitting Using Maximum Likelihood

Description

Predicted values based on a cusp model object.

Usage

## S3 method for class 'cusp'
predict(object, newdata, se.fit = FALSE, interval =
  c("none", "confidence", "prediction"), level = 0.95, type = c("response", "terms"),
  terms = NULL, na.action = na.pass, pred.var = res.var/weights, weights = 1,
  method = c("delay", "maxwell", "expected"), keep.linear.predictors = FALSE, ...)

Arguments

object	Object of class "cusp"
newdata	An optional data frame in which to look for variables with which to predict. If omitted, the fitted values are used.
se.fit	See predict.lm. Not yet used.
interval	See predict.lm. Not yet used.
level	See predict.lm. Not yet used.
type	See predict.lm. Not yet used.
terms	See predict.lm. Not yet used.
na.action	See predict.lm. Not yet used.
pred.var	See predict.lm. Not yet used.
weights	See predict.lm. Not yet used.
method	Type of prediction convention to use. Can be abbreviated. (expected should currently not be trusted).
keep.linear.predictors	Logical. Should the linear predictors (alpha, beta, and y) be returned?
...	further arguments passed to or from other methods.

Details

predict.cusp produces predicted values, obtained by evaluating the regression functions from the cusp object in the frame newdata using predict.lm. This results in linear predictors for the cusp control variables alpha, and beta, and, if method = "delay", for the behavioral cusp variable y. These are then used to compute predicted values: If method = "delay" these are the points y* on the cusp surface defined by

V'(y*) = α + β y* - y*^3 = 0

that are closest to y. If method = "maxwell" they are the points on the cusp surface corresponding to the minimum of the associated potential function V(y*) = α y* + 0.5 y*^2 - 0.25 y*^4.

Value

A vector of predictions. If keep.linear.predictors the return value has a "data" attribute which links to newdata augmented with the linear predictors alpha, beta, and, if method = "delay", y. If method = "expected", the expected value from the equilibrium distribution of the stochastic process

dY_t = V'(Y_t;α, β)dt + dW_t,

where W_t is a Wiener proces (aka Brownian motion) is returned. (This distribution is implemented in dcusp.)

Note

Currently method = "expected" should not be trusted.

Author(s)

Raoul Grasman

References

See cusp-package.

See Also

cusp-package, predict.lm.

Examples

set.seed(123)
# example with regressors
x1 = runif(150)
x2 = runif(150)
z = Vectorize(rcusp)(1, 4*x1-2, 4*x2-1)
data <- data.frame(x1, x2, z)
fit <- cusp(y ~ z, alpha ~ x1+x2, beta ~ x1+x2, data)

newdata = data.frame(x1 = runif(10), x2 = runif(10), z = 0)
predict(fit, newdata)

Example output

sh: 1: cannot create /dev/null: Permission denied
         Delay
1   0.63531173
2  -1.62147507
3  -0.41864306
4  -1.07699886
5   0.82419551
6  -1.02503152
7  -0.07647636
8  -0.84414590
9   1.03844952
10 -1.22409375

cusp documentation built on May 2, 2019, 6:51 p.m.