Print method for

Print method for "aplms" class

Usage

# S3 method for class 'aplms'
summary(object, ...)

Arguments

object: an object with the result of fitting additive partial linear models with symmetric errors.
...: Other arguments passed to or from other methods.

Value

Prints the main results of the fitted APLMS model.

Examples

data(temperature)
temperature.df = data.frame(temperature,time=1:length(temperature))
model<-aplms::aplms(temperature ~ 1,
                   npc=c("time"), basis=c("cr"),Knot=c(60),
                   data=temperature.df,family=Powerexp(k=0.3),p=1,
                   control = list(tol = 0.001,
                                  algorithm1 = c("P-GAM"),
                                  algorithm2 = c("BFGS"),
                                  Maxiter1 = 20,
                                  Maxiter2 = 25),
                   lam=c(10))
summary(model)
#>  ---------------------------------------------------------------
#>  Additive partial linear models with symmetric errors 
#>  ---------------------------------------------------------------
#>  Sample size:  142 
#>  -------------------------- Model ---------------------------
#> 
#> aplms::aplms(formula = temperature ~ 1, npc = c("time"), basis = c("cr"), 
#>     Knot = c(60), data = temperature.df, family = Powerexp(k = 0.3), 
#>     p = 1, control = list(tol = 0.001, algorithm1 = c("P-GAM"), 
#>         algorithm2 = c("BFGS"), Maxiter1 = 20, Maxiter2 = 25), 
#>     lam = c(10))
#>  
#>  ------------------- Parametric component -------------------
#> 
#>           Estimate Std. Error t value  Pr(>|t|)    
#> intercept 0.056619     0.0041 13.8905 < 2.2e-16 ***
#> 
#>  ----------------- Non-parametric component ------------------ 
#> 
#>          Wald       df    Pr(>.)    
#> time 7589.838   58.583 < 2.2e-16 ***
#> 
#>  --------------- Autoregressive and Scale parameter ---------------- 
#> 
#>        Estimate Std. Error    Wald  Pr(>|t|)    
#> phi   0.0022992     0.0003  7.3902 1.242e-11 ***
#> rho1 -0.2571215     0.0662 -3.8866 0.0001568 ***
#>  
#> 
#> ------ Penalized Log-likelihood and Information criterion------
#> 
#>  Log-lik:  200.07 
#>  AIC    :  -276.97 
#>  AICc   :  -274.46 
#>  BIC    :  -94.94 
#>  GCV    :  0.01 
#> 
#>  --------------------------------------------------------------------