diff options
Diffstat (limited to 'man')
| -rw-r--r-- | man/confint.mkinfit.Rd | 79 |
1 files changed, 72 insertions, 7 deletions
diff --git a/man/confint.mkinfit.Rd b/man/confint.mkinfit.Rd index b84facb8..99f5875c 100644 --- a/man/confint.mkinfit.Rd +++ b/man/confint.mkinfit.Rd @@ -7,7 +7,7 @@ \method{confint}{mkinfit}(object, parm, level = 0.95, alpha = 1 - level, cutoff, method = c("profile", "quadratic"), transformed = TRUE, backtransform = TRUE, - distribution = c("student_t", "normal"), quiet = FALSE, ...) + cores = round(detectCores()/2), quiet = FALSE, ...) } \arguments{ \item{object}{An \code{\link{mkinfit}} object} @@ -36,11 +36,11 @@ applied to the likelihood based on the transformed parameters?} transformed parameters, should we backtransform the parameters with their confidence intervals?} -\item{distribution}{For the quadratic approximation, should we use -the student t distribution or assume normal distribution for -the parameter estimate} +\item{cores}{The number of cores to be used for multicore processing. This +is only used when the \code{cluster} argument is \code{NULL}. On Windows +machines, cores > 1 is not supported.} -\item{quiet}{Should we suppress messages?} +\item{quiet}{Should we suppress the message "Profiling the likelihood"} \item{\dots}{Not used} } @@ -56,12 +56,77 @@ could likely be improved by using the method of Venzon and Moolgavkar (1988). \examples{ f <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE) confint(f, method = "quadratic") + \dontrun{ - confint(f, method = "profile") +confint(f, method = "profile") + +SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), quiet = TRUE) +SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), + use_of_ff = "max", quiet = TRUE) +f_d_1 <- mkinfit(SFO_SFO, subset(FOCUS_2006_D, value != 0), quiet = TRUE) +system.time(ci_profile <- confint(f_d_1, cores = 1, quiet = TRUE)) +# The following does not save much time, as parent_0 takes up most of the time +# system.time(ci_profile <- confint(f_d_1, cores = 5)) +# system.time(ci_profile <- confint(f_d_1, +# c("k_parent_sink", "k_parent_m1", "k_m1_sink", "sigma"), cores = 1)) +# If we exclude parent_0 (the confidence of which is often of minor interest), we get a nice +# performance improvement from about 30 seconds to about 12 seconds +# system.time(ci_profile_no_parent_0 <- confint(f_d_1, c("k_parent_sink", "k_parent_m1", "k_m1_sink", "sigma"), cores = 4)) +ci_profile +ci_quadratic_transformed <- confint(f_d_1, method = "quadratic") +ci_quadratic_transformed +ci_quadratic_untransformed <- confint(f_d_1, method = "quadratic", transformed = FALSE) +ci_quadratic_untransformed +# Against the expectation based on Bates and Watts (1988), the confidence +# intervals based on the internal parameter transformation are less +# congruent with the likelihood based intervals. Note the superiority of the +# interval based on the untransformed fit for k_m1_sink +rel_diffs_transformed <- abs((ci_quadratic_transformed - ci_profile)/ci_profile) +rel_diffs_untransformed <- abs((ci_quadratic_untransformed - ci_profile)/ci_profile) +rel_diffs_transformed +rel_diffs_untransformed + +# Set the number of cores for further examples +if (identical(Sys.getenv("NOT_CRAN"), "true")) { + n_cores <- parallel::detectCores() - 1 +} else { + n_cores <- 1 +} +if (Sys.getenv("TRAVIS") != "") n_cores = 1 +if (Sys.info()["sysname"] == "Windows") n_cores = 1 + +# Investigate a case with formation fractions +f_d_2 <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), quiet = TRUE) +ci_profile_ff <- confint(f_d_2, cores = n_cores) +ci_profile_ff +ci_quadratic_transformed_ff <- confint(f_d_2, method = "quadratic") +ci_quadratic_transformed_ff +ci_quadratic_untransformed_ff <- confint(f_d_2, method = "quadratic", transformed = FALSE) +ci_quadratic_untransformed_ff +rel_diffs_transformed_ff <- abs((ci_quadratic_transformed_ff - ci_profile_ff)/ci_profile_ff) +rel_diffs_untransformed_ff <- abs((ci_quadratic_untransformed_ff - ci_profile_ff)/ci_profile_ff) +# While the confidence interval for the parent rate constant is closer to +# the profile based interval when using the internal parameter +# transformation, the intervals for the other parameters are 'better +# without internal parameter transformation. +rel_diffs_transformed_ff +rel_diffs_untransformed_ff + +# The profiling for the following fit does not finish in a reasonable time +#m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")), +# M1 = mkinsub("SFO"), +# M2 = mkinsub("SFO"), +# use_of_ff = "max", quiet = TRUE) +#DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data +#f_tc_2 <- mkinfit(m_synth_DFOP_par, DFOP_par_c, error_model = "tc", +# error_model_algorithm = "direct", quiet = TRUE) +#confint(f_tc_2, "parent_0") } } \references{ -Pawitan Y (2013) In all likelihood - Statistical modelling and +Bates DM and Watts GW (1988) Nonlinear regression analysis & its applications + + Pawitan Y (2013) In all likelihood - Statistical modelling and inference using likelihood. Clarendon Press, Oxford. Venzon DJ and Moolgavkar SH (1988) A Method for Computing |