fit_pl: fit_pl

In cbg-ethz/WWdPCR: Analysis of Drop-Off Duplex dPCR Assays

Description

fit_pl

Usage

fit_pl(
  ydata,
  xdata,
  weights = 1,
  fitfun = pl3model,
  likelihood = loglik_binom_n,
  quasi = F,
  starting_values = c(a = 0.5, b = -10, c = 0.2),
  lower = c(-Inf, -Inf, 0),
  upper = c(Inf, Inf, 1)
)

## S3 method for class 'pl_fit'
coef(object, ...)

## S3 method for class 'pl_fit'
se(x)

## S3 method for class 'pl_fit'
fitted(object, ...)

## S3 method for class 'pl_fit'
confint(object, parm, level = 0.95, ...)

## S3 method for class 'pl_fit'
predict(object, newdata = NULL, scale = c("linear", "logit"), se = TRUE, ...)

## S3 method for class 'pl_fit'
logist_confint(x, newdata = NULL, level = 0.95, ...)

## S3 method for class 'pl_fit'
logist_predint(
  x,
  newdata = NULL,
  level = 0.95,
  likelihood = loglik_binom_n,
  ...
)

Arguments

ydata	response variable
xdata	independent variable
weights	weights vector (optional).
fitfun	fitting function
likelihood	likelihood function
quasi	compute overdispersion and use quasilikelihood model to build confidence intervals
starting_values	(named) vector of starting values for optimization
lower	vector of lower bounds for parameters
upper	vector of upper bounds for parameters
object	an object of class pl_fit
...	additional argument(s)
x	an object of class pl_fit
parm	a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
level	confidence level 1-alpha for prediction
newdata	an optional vector of observed independent variables with which to predict
scale	scale on which to predict, either linear or logit scale
se	whether to return the standard errors of the predictions or not

Value

pl_fit object

cbg-ethz/WWdPCR documentation built on Jan. 23, 2022, 2:45 p.m.