Some simple shortcuts to model fitting engines.

## BayesX.
bayesx2(...)

## Gradient boosting.
boost2(...)

## Lasso.
lasso2(...)

Arguments

...

Arguments passed to bamlss and predict.bamlss.

Value

A bamlss object.

See also

Examples

if (FALSE) ## Simulate data.
set.seed(123)
d <- GAMart()

## Estimate model.
f <- num ~ s(x1) + s(x2) + s(x3) + s(lon,lat)

## Boosted model.
b <- boost2(f, data = d)
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#> logLik 182.6109 eps 0.0019 iteration 363 qsel 4
#> logLik 182.6355 eps 0.0043 iteration 364 qsel 4
#> logLik 182.6442 eps 0.0002 iteration 365 qsel 4
#> logLik 182.6525 eps 0.0627 iteration 366 qsel 4
#> logLik 182.6679 eps 0.0037 iteration 367 qsel 4
#> logLik 182.6917 eps 0.0036 iteration 368 qsel 4
#> logLik 182.7268 eps 0.0020 iteration 369 qsel 4
#> logLik 182.7406 eps 0.0015 iteration 370 qsel 4
#> logLik 182.7579 eps 0.0021 iteration 371 qsel 4
#> logLik 182.7653 eps 0.0002 iteration 372 qsel 4
#> logLik 182.7725 eps 0.0023 iteration 373 qsel 4
#> logLik 182.8047 eps 0.0022 iteration 374 qsel 4
#> logLik 182.8166 eps 0.0015 iteration 375 qsel 4
#> logLik 182.8330 eps 0.0114 iteration 376 qsel 4
#> logLik 182.8555 eps 0.0029 iteration 377 qsel 4
#> logLik 182.8851 eps 0.0017 iteration 378 qsel 4
#> logLik 182.8916 eps 0.0020 iteration 379 qsel 4
#> logLik 182.9075 eps 0.0017 iteration 380 qsel 4
#> logLik 182.9267 eps 0.0058 iteration 381 qsel 4
#> logLik 182.9438 eps 0.0018 iteration 382 qsel 4
#> logLik 182.9590 eps 0.0026 iteration 383 qsel 4
#> logLik 182.9720 eps 0.0052 iteration 384 qsel 4
#> logLik 182.9914 eps 0.0025 iteration 385 qsel 4
#> logLik 182.9994 eps 0.0021 iteration 386 qsel 4
#> logLik 183.0135 eps 0.0030 iteration 387 qsel 4
#> logLik 183.0203 eps 0.0002 iteration 388 qsel 4
#> logLik 183.0259 eps 0.0002 iteration 389 qsel 4
#> logLik 183.0308 eps 0.0034 iteration 390 qsel 4
#> logLik 183.0482 eps 0.0024 iteration 391 qsel 4
#> logLik 183.0721 eps 0.0018 iteration 392 qsel 4
#> logLik 183.0853 eps 0.0034 iteration 393 qsel 4
#> logLik 183.1076 eps 0.0030 iteration 394 qsel 4
#> logLik 183.1198 eps 0.0028 iteration 395 qsel 4
#> logLik 183.1246 eps 0.0001 iteration 396 qsel 4
#> logLik 183.1290 eps 0.0028 iteration 397 qsel 4
#> logLik 183.1403 eps 0.0057 iteration 398 qsel 4
#> logLik 183.1542 eps 0.0025 iteration 399 qsel 4
#> logLik 183.1622 eps 0.0024 iteration 400 qsel 4
#> 
#>  elapsed time:  1.62sec


## Plot estimated effects.
plot(b)