x	An `mmkin object`
i	Row index selecting the fits for specific models
j	Column index selecting the fits to specific datasets
...	Not used, only there to satisfy the generic method definition
drop	If FALSE, the method always returns an mmkin object, otherwise either + a list of mkinfit objects or a single mkinfit object.

head( # The same can be achieved by @@ -188,7 +204,7 @@ #> 8 15 #> #> $counts -#> [1] "relative convergence (4)" +#> [1] "relative convergence (4)" #> #> $hessian #> parent_0 log_k_parent_sink @@ -223,7 +239,7 @@ #> [1] 6 #> #> $solution_type -#> [1] "analytical" +#> [1] "analytical" #> #> $transform_rates #> [1] TRUE @@ -232,17 +248,17 @@ #> [1] TRUE #> #> $method.modFit -#> [1] "Port" +#> [1] "Port" #> #> $maxit.modFit -#> [1] "auto" +#> [1] "auto" #> #> $calls #> [1] 29 #> #> $time #> user system elapsed -#> 0.068 0.000 0.066 +#> 0.064 0.000 0.063 #> #> $mkinmod #> <mkinmod> model generated with @@ -266,7 +282,7 @@ #> 8 parent 118 0.08 #> #> $obs_vars -#> [1] "parent" +#> [1] "parent" #> #> $predicted #> name time value @@ -380,9 +396,9 @@ #> $cost #> function (P) #> { -#> assign("calls", calls + 1, inherits = TRUE) +#> assign("calls", calls + 1, inherits = TRUE) #> if (trace_parms) -#> cat(P, "\n") +#> cat(P, "\n") #> if (length(state.ini.optim) > 0) { #> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) #> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) @@ -398,13 +414,13 @@ #> out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, #> use_compiled = use_compiled, method.ode = method.ode, #> atol = atol, rtol = rtol, ...) -#> assign("out_predicted", out, inherits = TRUE) -#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> assign("out_predicted", out, inherits = TRUE) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, #> scaleVar = scaleVar) #> if (mC$model < cost.old) { #> if (!quiet) -#> cat("Model cost at call ", calls, ": ", mC$model, -#> "\n") +#> cat("Model cost at call ", calls, ": ", mC$model, +#> "\n") #> if (plot) { #> outtimes_plot = seq(min(observed$time), max(observed$time), #> length.out = 100) @@ -412,9 +428,9 @@ #> solution_type = solution_type, use_compiled = use_compiled, #> method.ode = method.ode, atol = atol, rtol = rtol, #> ...) -#> plot(0, type = "n", xlim = range(observed$time), +#> plot(0, type = "n", xlim = range(observed$time), #> ylim = c(0, max(observed$value, na.rm = TRUE)), -#> xlab = "Time", ylab = "Observed") +#> xlab = "Time", ylab = "Observed") #> col_obs <- pch_obs <- 1:length(obs_vars) #> lty_obs <- rep(1, length(obs_vars)) #> names(col_obs) <- names(pch_obs) <- names(lty_obs) <- obs_vars @@ -424,14 +440,15 @@ #> } #> matlines(out_plot$time, out_plot[-1], col = col_obs, #> lty = lty_obs) -#> legend("topright", inset = c(0.05, 0.05), legend = obs_vars, +#> legend("topright", inset = c(0.05, 0.05), legend = obs_vars, #> col = col_obs, pch = pch_obs, lty = 1:length(pch_obs)) #> } -#> assign("cost.old", mC$model, inherits = TRUE) +#> assign("cost.old", mC$model, inherits = TRUE) #> } #> return(mC) #> } -#> <environment: 0x3b9eeb8> +#> <bytecode: 0x5554250> +#> <environment: 0x4eb4b18> #> #> $cost_notrans #> function (P) @@ -449,11 +466,12 @@ #> out <- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, #> use_compiled = use_compiled, method.ode = method.ode, #> atol = atol, rtol = rtol, ...) -#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, #> scaleVar = scaleVar) #> return(mC) #> } -#> <environment: 0x3b9eeb8> +#> <bytecode: 0x5073868> +#> <environment: 0x4eb4b18> #> #> $hessian_notrans #> parent_0 k_parent_sink @@ -492,7 +510,7 @@ #> [1] 1e-10 #> #> $weight.ini -#> [1] "none" +#> [1] "none" #> #> $reweight.tol #> [1] 1e-08 @@ -516,10 +534,10 @@ #> 99.17407 #> #> $date -#> [1] "Wed Mar 15 09:44:44 2017" +#> [1] "Fri May 5 12:44:53 2017" #> -#> attr(,"class") -#> [1] "mkinfit" "modFit" +#> attr(,"class") +#> [1] "mkinfit" "modFit" #>

Arguments

Value