cotram-methods: Methods for Count Transformation Models

In cotram: Count Transformation Models

Methods for Count Transformation Models

Description

Methods for objects inheriting from class cotram

Usage

## S3 method for class 'cotram'
predict(object, newdata = model.frame(object),
        type = c("lp", "trafo", "distribution", "survivor", "density", 
                 "logdensity", "hazard", "loghazard", "cumhazard", 
                 "logcumhazard", "odds", "logodds", "quantile"),
        smooth = FALSE, q = NULL, K = 20, prob = 1:(10-1)/10, ...)
## S3 method for class 'cotram'
plot(x, newdata, type = c("distribution", "survivor","density",
                          "logdensity", "cumhazard", "quantile", "trafo"),
        confidence = c("none", "band"), level = 0.95, 
        smooth = FALSE, q = NULL, K = 20, cheat = K, prob = 1:(10-1)/10,
        col = "black", fill = "lightgrey",
        lty = 1, lwd = 1, add = FALSE, ...) 
## S3 method for class 'cotram'
as.mlt(object)
## S3 method for class 'cotram'
logLik(object, parm = coef(as.mlt(object), fixed = FALSE), newdata, ...)

Arguments

object, x	a fitted linear count transformation model inheriting from class cotram.
newdata	an optional data frame of observations.
parm	model parameters.
type	type of prediction, current options include linear predictors ("lp", of x variables in the formula y ~ x), transformation functions ("trafo") or distribution functions on the scale of the cdf ("distribution"), survivor function, density function, log-density function, cumulative hazard function or quantile function.
confidence	whether to plot a confidence band (see confband).
level	the confidence level.
smooth	logical; if TRUE a smoothed function of type is returned.
q	quantiles at which to evaluate the model.
prob	probabilities for the evaluation of the quantile function (type = "quantile").
K	number of grid points the function is evaluated at (for smooth = TRUE and in absence of q).
cheat	number of grid points the function is evaluated at when using the quantile obtained for K grid points (in the absence of q and smooth = TRUE).
col	color for the lines to plot.
fill	color for the confidence band.
lty	line type for the lines to plot.
lwd	line width.
add	logical; indicating if a new plot shall be generated (the default).
...	additional arguments to the underlying methods for predict.

Details

predict and plot can be used to inspect the model on different scales.

See Also

predict.cotram, confband.cotram, tram-methods, mlt-methods, plot.ctm

Examples

  op <- options(digits = 4)

  data("birds", package = "TH.data")
  
  ### fit count transformation model with cloglog link
  m_birds <- cotram(SG5 ~ AOT + AFS + GST + DBH + DWC + LOG, data = birds,
                    method = "cloglog")
  logLik(m_birds)

  ### classical likelihood inference
## IGNORE_RDIFF_BEGIN
  summary(m_birds)
## IGNORE_RDIFF_END

  ### coefficients of the linear predictor (discrete hazard ratios)
  exp(-coef(m_birds))

  ### compute predicted median along with 10% and 90% quantile for the first
  ### three observations
  nd <- birds[1:3,]
  round(predict(m_birds, newdata = nd, type = "quantile", prob = c(.1, .5, .9), 
                smooth = TRUE), 3)

  ### plot the predicted distribution for these observations
  plot(m_birds, newdata = nd, type = "distribution",
       col = c("skyblue", "grey", "seagreen"))
       
  options(op)

cotram documentation built on Sept. 2, 2023, 3 a.m.