tidy.sdmTMB | R Documentation |
Turn sdmTMB model output into a tidy data frame
## S3 method for class 'sdmTMB'
tidy(
x,
effects = c("fixed", "ran_pars", "ran_vals"),
model = 1,
conf.int = FALSE,
conf.level = 0.95,
exponentiate = FALSE,
silent = FALSE,
...
)
x |
Output from |
effects |
A character value. One of |
model |
Which model to tidy if a delta model (1 or 2). |
conf.int |
Include a confidence interval? |
conf.level |
Confidence level for CI. |
exponentiate |
Whether to exponentiate the fixed-effect coefficient estimates and confidence intervals. |
silent |
Omit any messages? |
... |
Extra arguments (not used). |
Follows the conventions of the broom and broom.mixed packages.
Currently, effects = "ran_pars"
also includes dispersion-related terms
(e.g., phi
), which are not actually associated with random effects.
Standard errors for spatial variance terms fit in log space (e.g., variance terms, range, or parameters associated with the observation error) are omitted to avoid confusion. Confidence intervals are still available.
A data frame
fit <- sdmTMB(density ~ poly(depth_scaled, 2, raw = TRUE),
data = pcod_2011, mesh = pcod_mesh_2011,
family = tweedie()
)
tidy(fit)
tidy(fit, conf.int = TRUE)
tidy(fit, "ran_pars", conf.int = TRUE)
pcod_2011$fyear <- as.factor(pcod_2011$year)
fit <- sdmTMB(density ~ poly(depth_scaled, 2, raw = TRUE) + (1 | fyear),
data = pcod_2011, mesh = pcod_mesh_2011,
family = tweedie()
)
tidy(fit, "ran_vals")
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