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Diffstat (limited to 'man/nlme.mmkin.Rd')
| -rw-r--r-- | man/nlme.mmkin.Rd | 44 |
1 files changed, 37 insertions, 7 deletions
diff --git a/man/nlme.mmkin.Rd b/man/nlme.mmkin.Rd index 10c3ec78..0af670a0 100644 --- a/man/nlme.mmkin.Rd +++ b/man/nlme.mmkin.Rd @@ -77,16 +77,16 @@ have been obtained by fitting the same model to a list of datasets. \examples{ ds <- lapply(experimental_data_for_UBA_2019[6:10], function(x) subset(x$data[c("name", "time", "value")], name == "parent")) -f <- mmkin("SFO", ds, quiet = TRUE, cores = 1) +f <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, cores = 1) library(nlme) -endpoints(f[[1]]) -f_nlme <- nlme(f) -print(f_nlme) -endpoints(f_nlme) +f_nlme_sfo <- nlme(f["SFO", ]) +f_nlme_dfop <- nlme(f["DFOP", ]) +AIC(f_nlme_sfo, f_nlme_dfop) +print(f_nlme_dfop) +endpoints(f_nlme_dfop) \dontrun{ - f_nlme_2 <- nlme(f, start = c(parent_0 = 100, log_k_parent_sink = 0.1)) + f_nlme_2 <- nlme(f["SFO", ], start = c(parent_0 = 100, log_k_parent = 0.1)) update(f_nlme_2, random = parent_0 ~ 1) - # Test on some real data ds_2 <- lapply(experimental_data_for_UBA_2019[6:10], function(x) x$data[c("name", "time", "value")]) m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"), @@ -130,6 +130,36 @@ endpoints(f_nlme) endpoints(f_nlme_sfo_sfo) endpoints(f_nlme_dfop_sfo) + + if (findFunction("varConstProp")) { # tc error model for nlme available + # Attempts to fit metabolite kinetics with the tc error model + #f_2_tc <- mmkin(list("SFO-SFO" = m_sfo_sfo, + # "SFO-SFO-ff" = m_sfo_sfo_ff, + # "FOMC-SFO" = m_fomc_sfo, + # "DFOP-SFO" = m_dfop_sfo), + # ds_2, quiet = TRUE, + # error_model = "tc") + #f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ], control = list(maxIter = 100)) + #f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ]) + #f_nlme_dfop_sfo_tc <- update(f_nlme_dfop_sfo, weights = varConstProp(), + # control = list(sigma = 1, msMaxIter = 100, pnlsMaxIter = 15)) + # Fitting metabolite kinetics with nlme.mmkin and the two-component + # error model currently does not work, at least not with these data. + + f_tc <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, error_model = "tc") + f_nlme_sfo_tc <- nlme(f_tc["SFO", ]) + f_nlme_dfop_tc <- nlme(f_tc["DFOP", ]) + AIC(f_nlme_sfo, f_nlme_sfo_tc, f_nlme_dfop, f_nlme_dfop_tc) + print(f_nlme_dfop_tc) + } + f_2_obs <- mmkin(list("SFO-SFO" = m_sfo_sfo, + "DFOP-SFO" = m_dfop_sfo), + ds_2, quiet = TRUE, error_model = "obs") + f_nlme_sfo_sfo_obs <- nlme(f_2_obs["SFO-SFO", ]) + # The same with DFOP-SFO does not converge, apparently the variances of + # parent and A1 are too similar in this case, so that the model is + # overparameterised + #f_nlme_dfop_sfo_obs <- nlme(f_2_obs["DFOP-SFO", ], control = list(maxIter = 100)) } } \seealso{ |