Conditions for regional assessment under certain budget and cost values.

list_cond_R() constructs a list of possible regional species diversity assessment conditions under the specified budget and cost values.

Usage

list_cond_R(budget, lambda1, lambda2, lambda3, J = NULL, K = NULL)

Arguments

budget

A numeric specifying budget amount. The currency unit is arbitrary but must be consistent with that of lambda1, lambda2, and lambda3.

lambda1

A numeric specifying the cost per sequence read for high-throughput sequencing. The currency unit is arbitrary but must be consistent with that of budget, lambda2, and lambda3.

lambda2

A numeric specifying the cost per replicate for library preparation. The currency unit is arbitrary but must be consistent with that of budget, lambda1, and lambda3.

lambda3

A numeric specifying the visiting cost per site. The currency unit is arbitrary but must be consistent with that of budget, lambda1, and lambda2.

J

An optional vector for manually specifying the number of sites

K

An optional vector used to specify the number of replicates manually. For computational convenience, the K values must be in ascending order.

Value

A data frame containing columns named budget, lambda1, lambda2, lambda3, J, K, and N.

Details

This function can generate a data frame object to be given to the settings argument of eval_util_R(); see Examples of eval_util_R(). By default, it outputs a list of all feasible combinations of values for the number of sites J, number of replicates per site K, and sequencing depth per replicate N based on the given budget and cost values. The resulting N can be a non-integer because it is calculated simply by assuming that the maximum value can be obtained. If one wants to obtain a list for only a subset of the possible values of J and K under a given budget and cost value, use the J and/or K arguments (in fact, it is recommended that a relatively small number of K values be specified using the K argument because the list of all conditions achievable under moderate budget and cost values can be large, and it is rarely practical to have a vast number of replicates per site). If a given combination of J and K values is not feasible under the specified budget and cost values, the combination will be ignored and excluded from the output.