tidy.systemfit | R Documentation |
Tidy summarizes information about the components of a model. A model component might be a single term in a regression, a single hypothesis, a cluster, or a class. Exactly what tidy considers to be a model component varies across models but is usually self-evident. If a model has several distinct types of components, you will need to specify which components to return.
## S3 method for class 'systemfit'
tidy(x, conf.int = TRUE, conf.level = 0.95, ...)
x |
A |
conf.int |
Logical indicating whether or not to include a confidence
interval in the tidied output. Defaults to |
conf.level |
The confidence level to use for the confidence interval
if |
... |
Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in
|
This tidy method works with any model objects of class systemfit
.
Default returns a tibble of six columns.
A tibble::tibble()
with columns:
conf.high |
Upper bound on the confidence interval for the estimate. |
conf.low |
Lower bound on the confidence interval for the estimate. |
estimate |
The estimated value of the regression term. |
p.value |
The two-sided p-value associated with the observed statistic. |
std.error |
The standard error of the regression term. |
term |
The name of the regression term. |
tidy()
, systemfit::systemfit()
set.seed(27)
# load libraries for models and data
library(systemfit)
# generate data
df <- data.frame(
X = rnorm(100),
Y = rnorm(100),
Z = rnorm(100),
W = rnorm(100)
)
# fit model
fit <- systemfit(formula = list(Y ~ Z, W ~ X), data = df, method = "SUR")
# summarize model fit with tidiers
tidy(fit)
tidy(fit, conf.int = TRUE)
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