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Merge pull request #26 from UCD-SERG/typhoid_vignette_patch_11-11
possible fix for typhoid vignette
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@@ -10,3 +10,6 @@ docs | |
| src-i386 | ||
| src-x64 | ||
| ..Rcheck | ||
| serocalculator.Rcheck/ | ||
| serocalculator*.tar.gz | ||
| serocalculator*.tgz | ||
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| @@ -0,0 +1,125 @@ | ||
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| # | ||
| #' Age specific seroincidence function | ||
| #' This function models seroincidence using maximum likelihood estimation; that is, it finds the value of the seroincidence parameter which maximizes the likelihood (i.e., joint probability) of the data. | ||
| #' | ||
| #' @param dpop cross-sectional population data | ||
| #' @param c.age age category | ||
| #' @param start starting value for incidence rate | ||
| #' @param antigen_isos antigen isotypes: a [character()] vector of one or more antigen isotype names, which should match the values of the `antigen_iso` column in the `dpop` input argument | ||
| #' @param noise_params a [data.frame()] containing columns `nu`, etc. specifying conditional noise parameters | ||
| #' @param dmcmc mcmc samples from distribution of longitudinal decay curve parameters | ||
| #' @param verbose logical: if TRUE, print verbose log information to console | ||
| #' @param iterlim an [integer()], which provides an upper limit on the number of computational iterations used to search for the maximum likelihood estimate of incidence (passed to [stats::nlm()]). | ||
| #' @param stepmax a [numeric()], which limits how aggressively the [stats::nlm()] algorithm searches for the maximum likelihood estimate of incidence. If this function output an infinite standard error estimate, consider reducing this parameter. | ||
| #' @inheritParams postprocess_fit | ||
| #' @inheritParams stats::nlm | ||
| #' @inheritDotParams stats::nlm -f -p -hessian | ||
| #' | ||
| #' @return A [data.frame()] containing the following: | ||
| #' * `est.start`: the starting guess for incidence rate | ||
| #' * `ageCat`: the age category we are analyzing | ||
| #' * `incidence.rate`: the estimated incidence rate, per person year | ||
| #' * `CI.lwr`: lower limit of confidence interval for incidence rate | ||
| #' * `CI.upr`: upper limit of confidence interval for incidence rate | ||
| #' * `coverage`: coverage probability | ||
| #' * `neg.llik`: negative log-likelihood | ||
| #' * `iterations`: the number of iterations used | ||
| #' | ||
| #' @export | ||
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| est.incidence <- function( | ||
| dpop, | ||
| dmcmc, | ||
| noise_params, | ||
| c.age = NULL, | ||
| antigen_isos = dpop$antigen_iso |> unique(), | ||
| start = 0.1, | ||
| iterlim = 100, | ||
| coverage = .95, | ||
| verbose = FALSE, | ||
| stepmax = 1, | ||
| ...) | ||
| { | ||
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| lambda = start # initial estimate: starting value | ||
| log.lambda = log(lambda) | ||
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| if(!is.null(c.age)) | ||
| { | ||
| dpop = dpop %>% dplyr::filter(.data[["ageCat"]] == c.age) | ||
| dmcmc = dmcmc %>% dplyr::filter(.data[["ageCat"]] == c.age) | ||
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| if("ageCat" %in% names(noise_params)) | ||
| { | ||
| noise_params = | ||
| noise_params %>% | ||
| dplyr::filter(.data[["ageCat"]] == c.age) | ||
| } | ||
| } | ||
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| ps = list() | ||
| cs = list() | ||
| conds = list() | ||
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| for (cur_antigen in antigen_isos) | ||
| { | ||
| ps[[cur_antigen]] = get_xspd_one_antigen( | ||
| dpop = dpop, | ||
| antigen = cur_antigen) | ||
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| cs[[cur_antigen]] = get_curve_params_one_antigen( | ||
| params = dmcmc, | ||
| antigen = cur_antigen) | ||
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| conds[[cur_antigen]] = | ||
| noise_params %>% | ||
| dplyr::filter(.data[["antigen_iso"]] == cur_antigen) | ||
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| } | ||
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| # noise parameters | ||
| # cond.hlye.IgG | ||
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| objfunc = build_likelihood_function( | ||
| cross_sectional_data = ps, | ||
| longitudinal_parameter_samples = cs, | ||
| noise_params = conds) | ||
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| # seroincidence estimation | ||
| { | ||
| fit = nlm( | ||
| f = objfunc, | ||
| p = log.lambda, | ||
| hessian = TRUE, | ||
| iterlim = iterlim, | ||
| stepmax = stepmax, | ||
| ...) | ||
| } |> system.time() -> time | ||
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| if(verbose) | ||
| { | ||
| message('elapsed time: ') | ||
| print(time) | ||
| } | ||
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| if(fit$iterations >= iterlim) | ||
| { | ||
| warning( | ||
| "Maximum `nlm()` iterations reached; consider increasing `iterlim` argument.") | ||
| } | ||
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| log.lambda.est = | ||
| fit |> | ||
| postprocess_fit( | ||
| coverage = coverage, | ||
| start = start | ||
| ) |> | ||
| mutate( | ||
| ageCat = c.age, | ||
| antigen.iso = antigen_isos |> paste(collapse = "+")) %>% | ||
| structure( | ||
| noise.parameters = noise_params) | ||
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| return(log.lambda.est) | ||
| } |
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