This function takes a fitted `bayesx`

object and returns selection frequency tables of
model terms. These tables are only returned using the stepwise procedure in combination with
the bootstrap confidence intervals, see function `bayesx.control`

.

1 | ```
term.freqs(object, model = NULL, term = NULL, ...)
``` |

`object` |
an object of class |

`model` |
for which model the tables should be provided, either an integer or a character,
e.g. |

`term` |
character or integer. The term for which the frequency table should be extracted. |

`...` |
not used. |

Nikolaus Umlauf, Thomas Kneib, Stefan Lang, Achim Zeileis.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ```
## Not run:
## generate some data
set.seed(111)
n <- 500
## regressors
dat <- data.frame(x = runif(n, -3, 3), z = runif(n, -1, 1),
w = runif(n, 0, 1), fac = factor(rep(1:10, n/10)))
## response
dat$y <- with(dat, 1.5 + sin(x) + rnorm(n, sd = 0.6))
## estimate model
b <- bayesx(y ~ sx(x) + sx(z) + sx(w) + sx(fac, bs = "re"),
method = "STEP", CI = "MCMCbootstrap", bootstrapsamples = 99,
data = dat)
summary(b)
## extract frequency tables
term.freqs(b)
## End(Not run)
``` |

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