#' @param chains (positive integer) The number of Markov chains to run. The
#' default is 4.
#' @param parallel_chains (positive integer) The _maximum_ number of MCMC chains
#' to run in parallel. If `parallel_chains` is not specified then the default
#' is to look for the option `"mc.cores"`, which can be set for an entire \R
#' session by `options(mc.cores=value)`. If the `"mc.cores"` option has not
#' been set then the default is `1`.
#' @param chain_ids (integer vector) A vector of chain IDs. Must contain as many
#' unique positive integers as the number of chains. If not set, the default
#' chain IDs are used (integers starting from `1`).
#' @param threads_per_chain (positive integer) If the model was
#' [compiled][model-method-compile] with threading support, the number of
#' threads to use in parallelized sections _within_ an MCMC chain (e.g., when
#' using the Stan functions `reduce_sum()` or `map_rect()`). This is in
#' contrast with `parallel_chains`, which specifies the number of chains to
#' run in parallel. The actual number of CPU cores used is
#' `parallel_chains*threads_per_chain`. For an example of using threading see
#' the Stan case study [Reduce Sum: A Minimal
#' Example](https://mc-stan.org/users/documentation/case-studies/reduce_sum_tutorial.html).
#'
#' @param iter_sampling (positive integer) The number of post-warmup iterations
#' to run per chain. Note: in the CmdStan User's Guide this is referred to as
#' `num_samples`.
#' @param iter_warmup (positive integer) The number of warmup iterations to run
#' per chain. Note: in the CmdStan User's Guide this is referred to as
#' `num_warmup`.
#' @param save_warmup (logical) Should warmup iterations be saved? The default
#' is `FALSE`.
#' @param thin (positive integer) The period between saved samples. This should
#' typically be left at its default (no thinning) unless memory is a problem.
#' @param max_treedepth (positive integer) The maximum allowed tree depth for
#' the NUTS engine. See the _Tree Depth_ section of the CmdStan User's Guide
#' for more details.
#' @param adapt_engaged (logical) Do warmup adaptation? The default is `TRUE`.
#' If a precomputed inverse metric is specified via the `inv_metric` argument
#' (or `metric_file`) then, if `adapt_engaged=TRUE`, Stan will use the
#' provided inverse metric just as an initial guess during adaptation. To turn
#' off adaptation when using a precomputed inverse metric set
#' `adapt_engaged=FALSE`.
#' @param adapt_delta (real in `(0,1)`) The adaptation target acceptance
#' statistic.
#' @param step_size (positive real) The _initial_ step size for the discrete
#' approximation to continuous Hamiltonian dynamics. This is further tuned
#' during warmup.
#' @param metric (string) One of `"diag_e"`, `"dense_e"`, or `"unit_e"`,
#' specifying the geometry of the base manifold. See the _Euclidean Metric_
#' section of the CmdStan User's Guide for more details. To specify a
#' precomputed (inverse) metric, see the `inv_metric` argument below.
#' @param metric_file (character vector) The paths to JSON or Rdump files (one
#' per chain) compatible with CmdStan that contain precomputed inverse
#' metrics. The `metric_file` argument is inherited from CmdStan but is
#' confusing in that the entry in JSON or Rdump file(s) must be named
#' `inv_metric`, referring to the _inverse_ metric. We recommend instead using
#' CmdStanR's `inv_metric` argument (see below) to specify an inverse metric
#' directly using a vector or matrix from your \R session.
#' @param inv_metric (vector, matrix) A vector (if `metric='diag_e'`) or a
#' matrix (if `metric='dense_e'`) for initializing the inverse metric. This
#' can be used as an alternative to the `metric_file` argument. A vector is
#' interpreted as a diagonal metric. The inverse metric is usually set to an
#' estimate of the posterior covariance. See the `adapt_engaged` argument
#' above for details about (and control over) how specifying a precomputed
#' inverse metric interacts with adaptation.
#' @param init_buffer (nonnegative integer) Width of initial fast timestep
#' adaptation interval during warmup.
#' @param term_buffer (nonnegative integer) Width of final fast timestep
#' adaptation interval during warmup.
#' @param window (nonnegative integer) Initial width of slow timestep/metric
#' adaptation interval.
#' @param fixed_param (logical) When `TRUE`, call CmdStan with argument
#' `"algorithm=fixed_param"`. The default is `FALSE`. The fixed parameter
#' sampler generates a new sample without changing the current state of the
#' Markov chain; only generated quantities may change. This can be useful
#' when, for example, trying to generate pseudo-data using the generated
#' quantities block. If the parameters block is empty then using
#' `fixed_param=TRUE` is mandatory. When `fixed_param=TRUE` the `chains` and
#' `parallel_chains` arguments will be set to `1`.
#' @param diagnostics (character vector) The diagnostics to automatically check
#' and warn about after sampling. Setting this to an empty string `""` or
#' `NULL` can be used to prevent CmdStanR from automatically reading in the
#' sampler diagnostics from CSV if you wish to manually read in the results
#' and validate them yourself, for example using [read_cmdstan_csv()]. The
#' currently available diagnostics are `"divergences"`, `"treedepth"`, and
#' `"ebfmi"` (the default is to check all of them).
#'
#' These diagnostics are also available after fitting. The
#' [`$sampler_diagnostics()`][fit-method-sampler_diagnostics] method provides
#' access the diagnostic values for each iteration and the
#' [`$diagnostic_summary()`][fit-method-diagnostic_summary] method provides
#' summaries of the diagnostics and can regenerate the warning messages.
#'
#' Diagnostics like R-hat and effective sample size are _not_ currently
#' available via the `diagnostics` argument but can be checked after fitting
#' using the [`$summary()`][fit-method-summary] method.
#' @param save_metric (logical) When `TRUE`, call CmdStan with argument
#' `"adaptation save_metric=1"` to save the adapted metric in separate JSON
#' file with elements "stepsize", "metric_type" and "inv_metric". The default
#' is `TRUE`. This option is only available in CmdStan 2.34.0 and later.
#'
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