Some Shortcuts

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

bamlss, boost, lasso, BayesX

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 182.5736 eps 0.0029 iteration 362 qsel 4
#> logLik 182.6115 eps 0.0020 iteration 363 qsel 4
#> logLik 182.6362 eps 0.0044 iteration 364 qsel 4
#> logLik 182.6493 eps 0.0015 iteration 365 qsel 4
#> logLik 182.6580 eps 0.0002 iteration 366 qsel 4
#> logLik 182.6659 eps 0.0060 iteration 367 qsel 4
#> logLik 182.6888 eps 0.0035 iteration 368 qsel 4
#> logLik 182.7242 eps 0.0016 iteration 369 qsel 4
#> logLik 182.7426 eps 0.0022 iteration 370 qsel 4
#> logLik 182.7756 eps 0.0019 iteration 371 qsel 4
#> logLik 182.7831 eps 0.0002 iteration 372 qsel 4
#> logLik 182.7902 eps 0.0020 iteration 373 qsel 4
#> logLik 182.8052 eps 0.0021 iteration 374 qsel 4
#> logLik 182.8221 eps 0.0091 iteration 375 qsel 4
#> logLik 182.8414 eps 0.0032 iteration 376 qsel 4
#> logLik 182.8611 eps 0.0037 iteration 377 qsel 4
#> logLik 182.8741 eps 0.0016 iteration 378 qsel 4
#> logLik 182.9020 eps 0.0026 iteration 379 qsel 4
#> logLik 182.9085 eps 0.0002 iteration 380 qsel 4
#> logLik 182.9148 eps 0.0020 iteration 381 qsel 4
#> logLik 182.9355 eps 0.0063 iteration 382 qsel 4
#> logLik 182.9446 eps 0.0017 iteration 383 qsel 4
#> logLik 182.9624 eps 0.0034 iteration 384 qsel 4
#> logLik 182.9887 eps 0.0037 iteration 385 qsel 4
#> logLik 182.9945 eps 0.0032 iteration 386 qsel 4
#> logLik 183.0106 eps 0.0067 iteration 387 qsel 4
#> logLik 183.0353 eps 0.0027 iteration 388 qsel 4
#> logLik 183.0502 eps 0.0046 iteration 389 qsel 4
#> logLik 183.0647 eps 0.0028 iteration 390 qsel 4
#> logLik 183.0755 eps 0.0025 iteration 391 qsel 4
#> logLik 183.0941 eps 0.0025 iteration 392 qsel 4
#> logLik 183.1001 eps 0.0016 iteration 393 qsel 4
#> logLik 183.1133 eps 0.0026 iteration 394 qsel 4
#> logLik 183.1297 eps 0.0021 iteration 395 qsel 4
#> logLik 183.1356 eps 0.0002 iteration 396 qsel 4
#> logLik 183.1403 eps 0.0002 iteration 397 qsel 4
#> logLik 183.1445 eps 0.3172 iteration 398 qsel 4
#> logLik 183.1652 eps 0.0021 iteration 399 qsel 4
#> logLik 183.1759 eps 0.0055 iteration 400 qsel 4
#> 
#>  elapsed time:  1.10sec


## Plot estimated effects.
plot(b)