View source: R/biglm-tidiers.R
| tidy.biglm | 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 'biglm' tidy(x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, ...)
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   | 
exponentiate | 
 Logical indicating whether or not to exponentiate the
the coefficient estimates. This is typical for logistic and multinomial
regressions, but a bad idea if there is no log or logit link. Defaults
to   | 
... | 
 Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in  
  | 
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.  | 
statistic | 
 The value of a T-statistic to use in a hypothesis that the regression term is non-zero.  | 
std.error | 
 The standard error of the regression term.  | 
term | 
 The name of the regression term.  | 
tidy(), biglm::biglm(), biglm::bigglm()
Other biglm tidiers: 
glance.biglm()
# load modeling library library(biglm) # fit model -- linear regression bfit <- biglm(mpg ~ wt + disp, mtcars) # summarize model fit with tidiers tidy(bfit) tidy(bfit, conf.int = TRUE) tidy(bfit, conf.int = TRUE, conf.level = .9) glance(bfit) # fit model -- logistic regression bgfit <- bigglm(am ~ mpg, mtcars, family = binomial()) # summarize model fit with tidiers tidy(bgfit) tidy(bgfit, exponentiate = TRUE) tidy(bgfit, conf.int = TRUE) tidy(bgfit, conf.int = TRUE, conf.level = .9) tidy(bgfit, conf.int = TRUE, conf.level = .9, exponentiate = TRUE) glance(bgfit)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.