Returns the powers of the GLM fitted model which has the lowest deviance score.

Refers to section 6.2.

Usage

find_best_fp_powers(data, p, mc, degree, link = "logit")

Arguments

data

the input data frame, must either have `age`, `pos`, `tot` columns (for aggregated data) OR `age`, `status` for (linelisting data)

p

a powers sequence.

mc

indicates if the returned model should be monotonic.

degree

the degree of the model. Recommended to be <= 2.

link

the link function. Defaulted to "logit".

Value

list of 3 elements:

p

The best power for fp model.

deviance

Deviance of the best fitted model.

model

The best model fitted

Examples

df <- hav_be_1993_1994
best_p <- find_best_fp_powers(
df,
p=seq(-2,3,0.1), mc=FALSE, degree=2, link="cloglog"
)
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best_p
#> $p
#> [1] 1.5 1.6
#> 
#> $deviance
#> [1] 81.60333
#> 
#> $model
#> 
#> Call:  glm(formula = as.formula(formulate(p_cur)), family = binomial(link = link))
#> 
#> Coefficients:
#> (Intercept)   I(age^1.5)   I(age^1.6)  
#>    -3.61083      0.12443     -0.07656  
#> 
#> Degrees of Freedom: 85 Total (i.e. Null);  83 Residual
#> Null Deviance:	    1320 
#> Residual Deviance: 81.6 	AIC: 361.2
#>