Fitted point-process model object — ldmppr

Objects of class ldmppr_fit are returned by estimate_process_parameters. They contain the best-fitting optimization result (and optionally multiple fits, e.g. from a delta search) along with metadata used to reproduce the fit.

Usage

# S3 method for class 'ldmppr_fit'
print(x, ...)

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

# S3 method for class 'ldmppr_fit'
logLik(object, ...)

# S3 method for class 'ldmppr_fit'
summary(object, ...)

# S3 method for class 'summary.ldmppr_fit'
print(x, ...)

# S3 method for class 'ldmppr_fit'
plot(x, ...)

as_nloptr(x, ...)

# S3 method for class 'ldmppr_fit'
as_nloptr(x, ...)

Arguments

x: an object of class ldmppr_fit.
...: additional arguments (not used).
object: an object of class ldmppr_fit.

Value

print(): prints a brief summary of the fit.
coef(): returns the estimated parameter vector.
logLik(): returns the log-likelihood at the optimum.
summary(): returns a summary.ldmppr_fit.
plot(): plots diagnostics for multi-fit runs, if available.

Details

A ldmppr_fit is a list with (at minimum):

process: process name (e.g. "self_correcting")
fit: best optimization result (currently an nloptr object)
mapping: mapping information (e.g. chosen delta, objectives)
grid: grid definitions used by likelihood approximation

Methods (by generic)

print(ldmppr_fit): Print a brief summary of a fitted model.
coef(ldmppr_fit): Extract the estimated parameter vector.
logLik(ldmppr_fit): Log-likelihood at the optimum.
summary(ldmppr_fit): Summarize a fitted model.
plot(ldmppr_fit): Plot diagnostics for a fitted model.
as_nloptr(ldmppr_fit): Extract the underlying nloptr result.

Functions

print(summary.ldmppr_fit): Print a summary produced by summary.ldmppr_fit.
as_nloptr(): Extract the underlying nloptr result.