confint.SSN2: Confidence intervals for fitted model parameters

In SSN2: Spatial Modeling on Stream Networks

Confidence intervals for fitted model parameters

Description

Computes confidence intervals for one or more parameters in a fitted model object.

Usage

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

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

Arguments

object	A fitted model object from ssn_lm() or ssn_glm().
parm	A specification of which parameters are to be given confidence intervals (a character vector of names). If missing, all parameters are considered.
level	The confidence level required. The default is 0.95.
...	Other arguments. Not used (needed for generic consistency).

Value

Gaussian-based confidence intervals (two-sided and equal-tailed) for the fixed effect coefficients based on the confidence level specified by level. For ssn_glm() objects, confidence intervals are on the link scale.

Examples

# Copy the mf04p .ssn data to a local directory and read it into R
# When modeling with your .ssn object, you will load it using the relevant
# path to the .ssn data on your machine
copy_lsn_to_temp()
temp_path <- paste0(tempdir(), "/MiddleFork04.ssn")
mf04p <- ssn_import(temp_path, overwrite = TRUE)

ssn_mod <- ssn_lm(
  formula = Summer_mn ~ ELEV_DEM,
  ssn.object = mf04p,
  tailup_type = "exponential",
  additive = "afvArea"
)
confint(ssn_mod)
confint(ssn_mod, level = 0.9)

SSN2 documentation built on May 29, 2024, 4:41 a.m.