Create the controls list for the Time Series model

This function provides a simple creation and definition of a list used to control the time series model fit occurring within TS.

TS_control(memoise = TRUE, response = "gamma", lambda = 0,
  measurer = AIC, selector = min, ntemps = 6,
  penultimate_temp = 2^6, ultimate_temp = 1e+10, q = 0,
  nit = 10000, magnitude = 12, quiet = FALSE, burnin = 0,
  thin_frac = 1, summary_prob = 0.95, seed = NULL)

Arguments

memoise	logical indicator of whether the multinomial functions should be memoised (via memoise). Memoisation happens to both multinom_TS and multinom_TS_chunk.
response	character element indicating the response variable used in the time series.
lambda	numeric "weight" decay term used to set the prior on the regressors within each chunk-level model. Defaults to 0, corresponding to a fully vague prior.
measurer, selector	Function names for use in evaluation of the TS models. measurer is used to create a value for each model and selector operates on the values to choose the model.
ntemps	integer number of temperatures (chains) to use in the ptMCMC algorithm.
penultimate_temp	Penultimate temperature in the ptMCMC sequence.
ultimate_temp	Ultimate temperature in the ptMCMC sequence.
q	Exponent controlling the ptMCMC temperature sequence from the focal chain (reference with temperature = 1) to the penultimate chain. 0 (default) implies a geometric sequence. 1 implies squaring before exponentiating.
nit	integer number of iterations (steps) used in the ptMCMC algorithm.
magnitude	Average magnitude (defining a geometric distribution) for the proposed step size in the ptMCMC algorithm.
quiet	logical indicator of whether the model should run quietly (if FALSE, a progress bar and notifications are printed).
burnin	integer number of iterations to remove from the beginning of the ptMCMC algorithm.
thin_frac	Fraction of iterations to retain, must be \((0, 1]\), and the default value of 1 represents no thinning.
summary_prob	Probability used for summarizing the posterior distributions (via the highest posterior density interval, see HPDinterval).
seed	Input to set.seed for replication purposes.

Value

list, with named elements corresponding to the arguments.

Examples

  TS_control()