cotram (version 0.5-2)

cotram-methods: Methods for Count Transformation Models

Description

Methods for objects inheriting from class cotram

Usage

# S3 method for 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 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 cotram
as.mlt(object)
# S3 method for 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
  summary(m_birds)

  ### 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)