Description Usage Arguments Examples

View source: R/find_dfa_trends.R

Fit a DFA with different number of trends and return the leave one out (LOO) value as calculated by the loo package.

1 2 3 4 5 6 7 8 9 10 11 | ```
find_dfa_trends(
y = y,
kmin = 1,
kmax = 5,
iter = 2000,
thin = 1,
compare_normal = FALSE,
convergence_threshold = 1.05,
variance = c("equal", "unequal"),
...
)
``` |

`y` |
A matrix of data to fit. Columns represent time element. |

`kmin` |
Minimum number of trends, defaults to 1. |

`kmax` |
Maximum number of trends, defaults to 5. |

`iter` |
Iterations when sampling from each Stan model, defaults to 2000. |

`thin` |
Thinning rate when sampling from each Stan model, defaults to 1. |

`compare_normal` |
If |

`convergence_threshold` |
The maximum allowed value of Rhat to determine convergence of parameters |

`variance` |
Vector of variance arguments for searching over large groups of models. Can be either or both of ("equal","unequal") |

`...` |
Other arguments to pass to |

1 2 3 4 5 6 7 8 9 10 11 | ```
set.seed(42)
s <- sim_dfa(num_trends = 2, num_years = 20, num_ts = 3)
# only 1 chain and 180 iterations used so example runs quickly:
m <- find_dfa_trends(
y = s$y_sim, iter = 50,
kmin = 1, kmax = 2, chains = 1, compare_normal = FALSE,
variance = "equal", convergence_threshold = 1.1,
control = list(adapt_delta = 0.95, max_treedepth = 20)
)
m$summary
m$best_model
``` |

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