From 9298a503d8de99dad1f61d6eb8bc228dd4acce6b Mon Sep 17 00:00:00 2001
From: Johannes Ranke
saemix_model(object, cores = parallel::detectCores()) +saemix_model(object, cores = 1) saemix_data(object, ...)@@ -162,12 +162,15 @@ a list of datasets.object -+ An mmkin row object containing several fits of the same model to different datasets
An mmkin row object containing several fits of the same model +to different datasets
cores -+ The number of cores to be used for multicore processing. -On Windows machines, cores > 1 is currently not supported.
The number of cores to be used for multicore processing using +
parallel::mclapply()
. Using more than 1 core is experimental and may +lead to uncontrolled forking, apparently depending on the BLAS version +used.... @@ -237,8 +240,8 @@ variances of the deviations of the parameters from these mean values. #> res <- unlist(res_list) #> return(res) #> } -#> <bytecode: 0x555555c89340> -#> <environment: 0x555555c82680> +#> <bytecode: 0x55555d62aeb8> +#> <environment: 0x55555e35c170> #> Nb of parameters: 4 #> parameter names: parent_0 log_k_parent log_k_A1 f_parent_ilr_1 #> distribution: @@ -271,10 +274,10 @@ variances of the deviations of the parameters from these mean values. nbiter.saemix = c(200, 80)) f_saemix <- saemix(m_saemix, d_saemix, saemix_options)#> Running main SAEM algorithm -#> [1] "Thu Oct 15 14:51:26 2020" +#> [1] "Thu Nov 5 08:26:39 2020" #> .. #> Minimisation finished -#> [1] "Thu Oct 15 14:53:18 2020"#> Nonlinear mixed-effects model fit by the SAEM algorithm +#> [1] "Thu Nov 5 08:28:33 2020"#> Nonlinear mixed-effects model fit by the SAEM algorithm #> ----------------------------------- #> ---- Data ---- #> ----------------------------------- @@ -338,8 +341,8 @@ variances of the deviations of the parameters from these mean values. #> res <- unlist(res_list) #> return(res) #> } -#> <bytecode: 0x555555c89340> -#> <environment: 0x555555c82680> +#> <bytecode: 0x55555d62aeb8> +#> <environment: 0x55555e35c170> #> Nb of parameters: 4 #> parameter names: parent_0 log_k_parent log_k_A1 f_parent_ilr_1 #> distribution: @@ -483,8 +486,8 @@ variances of the deviations of the parameters from these mean values. #> res <- unlist(res_list) #> return(res) #> } -#> <bytecode: 0x555555c89340> -#> <environment: 0x55555df58cf8> +#> <bytecode: 0x55555d62aeb8> +#> <environment: 0x55555cd8e028> #> Nb of parameters: 2 #> parameter names: parent_0 log_k_parent #> distribution: @@ -510,10 +513,10 @@ variances of the deviations of the parameters from these mean values. #> Structured data: value ~ time + name | ds #> X variable for graphs: time ()#> Running main SAEM algorithm -#> [1] "Thu Oct 15 14:53:35 2020" +#> [1] "Thu Nov 5 08:28:50 2020" #> .. #> Minimisation finished -#> [1] "Thu Oct 15 14:54:25 2020"#> Nonlinear mixed-effects model fit by the SAEM algorithm +#> [1] "Thu Nov 5 08:29:41 2020"#> Nonlinear mixed-effects model fit by the SAEM algorithm #> ----------------------------------- #> ---- Data ---- #> ----------------------------------- @@ -577,8 +580,8 @@ variances of the deviations of the parameters from these mean values. #> res <- unlist(res_list) #> return(res) #> } -#> <bytecode: 0x555555c89340> -#> <environment: 0x55555df58cf8> +#> <bytecode: 0x55555d62aeb8> +#> <environment: 0x55555cd8e028> #> Nb of parameters: 2 #> parameter names: parent_0 log_k_parent #> distribution: -- cgit v1.2.1