Description Usage Arguments Details Value Author(s) References See Also Examples
Predicts values for the given object, if a new predictor is given.
1 2 3 |
object |
Object of class flexgam. |
linear.predictor |
New predictor, which has to be centered and scaled properly. |
... |
Currently not used |
Calculates predicted values for the given model. Used to get the estimated response function separately from the covariate effects. For the same predictor predict.flexgam(...,type="response")
and response(...)
are equal.
Numeric vector of fitted values.
Elmar Spiegel
Spiegel, Elmar, Thomas Kneib and Fabian Otto-Sobotka. Generalized additive models with flexible response functions. Statistics and Computing (2017). https://doi.org/10.1007/s11222-017-9799-6
flexgam
, deviance.flexgam
, predict.flexgam
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 28 29 30 31 32 33 34 35 36 37 38 | set.seed(1)
n <- 1000
x1 <- runif(n)
x2 <- runif(n)
x3 <- runif(n)
eta_orig <- -1 + 2*sin(6*x1) + exp(x2) + x3
pi_orig <- pgamma(eta_orig, shape=2, rate=sqrt(2))
y <- rbinom(n,size=1,prob=pi_orig)
Data <- data.frame(y,x1,x2,x3)
formula <- y ~ s(x1,k=20,bs="ps") + s(x2,k=20,bs="ps") + x3
# Fix smoothing parameters to save computational time.
control2 <- list("fix_smooth" = TRUE, "quietly" = TRUE, "sm_par_vec" =
c("lambda" = 100, "s(x1)" = 2000, "s(x2)" = 9000))
set.seed(2)
model_2 <- flexgam(formula=formula, data=Data, type="FlexGAM2",
family=binomial(link=logit), control = control2)
set.seed(2)
n <- 1000
x1 <- runif(n)
x2 <- runif(n)
x3 <- runif(n)
eta_orig <- -1 + 2*sin(6*x1) + exp(x2) + x3
pi_orig <- pgamma(eta_orig, shape=2, rate=sqrt(2))
y <- rbinom(n,size=1,prob=pi_orig)
newData <- data.frame(y,x1,x2,x3)
fitted_1 <- predict(model_2, newdata=newData, type="response")
predictor1 <- predict(model_2, newdata=newData, type="linear.predictor")
fitted_2 <- response(model_2, linear.predictor=predictor1)
all.equal(fitted_1,fitted_2)
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