`summary()` method for `fastglm` fitted objects

`summary()` method for `fastglm` fitted objects

# S3 method for class 'fastglm'
summary(object, dispersion = NULL, ...)

Arguments

object

`fastglm` fitted object

dispersion

the dispersion parameter for the family used. Either a single numerical value or `NULL` (the default), when it is inferred from `object`.

...

not used

Value

A `summary.fastglm` object

See also

[summary.glm()]

Examples

x <- matrix(rnorm(10000 * 10), ncol = 10)
y <- 1 * (0.25 * x[,1] - 0.25 * x[,3] > rnorm(10000))

fit <- fastglm(x, y, family = binomial())

summary(fit)
#> 
#> Call:
#> fastglm.default(x = x, y = y, family = binomial())
#> 
#> Coefficients:
#>       Estimate Std. Error z value Pr(>|z|)    
#> X1   4.245e-01  2.141e-02  19.827   <2e-16 ***
#> X2  -2.902e-02  2.047e-02  -1.418    0.156    
#> X3  -3.647e-01  2.132e-02 -17.107   <2e-16 ***
#> X4   7.534e-03  2.089e-02   0.361    0.718    
#> X5  -3.794e-03  2.063e-02  -0.184    0.854    
#> X6   2.654e-02  2.080e-02   1.276    0.202    
#> X7  -9.933e-03  2.059e-02  -0.482    0.630    
#> X8   6.531e-03  2.087e-02   0.313    0.754    
#> X9   6.044e-05  2.056e-02   0.003    0.998    
#> X10  2.260e-02  2.079e-02   1.087    0.277    
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#> 
#> (Dispersion parameter for binomial family taken to be 1)
#> 
#>     Null deviance: 13863  on 10000  degrees of freedom
#> Residual deviance: 13150  on  9990  degrees of freedom
#> AIC: 13170
#> 
#> Number of Fisher Scoring iterations: 4
#>