diff options
| author | Johannes Ranke <jranke@uni-bremen.de> | 2020-04-15 18:13:04 +0200 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2020-04-15 19:00:06 +0200 |
| commit | 42171ba55222383a0d47e5aacd46a972819e7812 (patch) | |
| tree | 190320919fe83aece30b654bfeb7687241e36f99 /docs/reference/nlme.mmkin.html | |
| parent | 637bd14fed5ab8a615f0d879012f12c59e1532a4 (diff) | |
Include random effects in starting parameters
- mean_degparms() now optionally returns starting values for fixed and
random effects, which makes it possible to obtain acceptable fits
also in more difficult cases (with more parameters)
- Fix the anova method, as it is currently not enough to inherit from
lme: https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17761
- Show fit information, and per default also errmin information
in plot.nlme.mmkin()
- Examples for nlme.mmkin: Decrease tolerance and increase the number of
iterations in the PNLS step in order to be able to fit FOMC-SFO and
DFOP-SFO
Diffstat (limited to 'docs/reference/nlme.mmkin.html')
| -rw-r--r-- | docs/reference/nlme.mmkin.html | 172 |
1 files changed, 159 insertions, 13 deletions
diff --git a/docs/reference/nlme.mmkin.html b/docs/reference/nlme.mmkin.html index e1b1ff77..01287dda 100644 --- a/docs/reference/nlme.mmkin.html +++ b/docs/reference/nlme.mmkin.html @@ -156,7 +156,13 @@ have been obtained by fitting the same model to a list of datasets.</p> <span class='no'>naPattern</span>, <span class='kw'>control</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(), <span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>FALSE</span> -)</pre> +) + +<span class='co'># S3 method for nlme.mmkin</span> +<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>x</span>, <span class='no'>...</span>) + +<span class='co'># S3 method for nlme.mmkin</span> +<span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span>(<span class='no'>object</span>, <span class='no'>...</span>)</pre> <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> <table class="ref-arguments"> @@ -167,7 +173,7 @@ have been obtained by fitting the same model to a list of datasets.</p> </tr> <tr> <th>data</th> - <td><p>Ignored, data are taken from the mmkin model</p></td> + <td><p>Should the data be printed?</p></td> </tr> <tr> <th>fixed</th> @@ -220,6 +226,18 @@ parameters taken from the mmkin object are used</p></td> <th>verbose</th> <td><p>passed to nlme</p></td> </tr> + <tr> + <th>x</th> + <td><p>An nlme.mmkin object to print</p></td> + </tr> + <tr> + <th>...</th> + <td><p>Update specifications passed to update.nlme</p></td> + </tr> + <tr> + <th>object</th> + <td><p>An nlme.mmkin object to update</p></td> + </tr> </table> <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> @@ -236,24 +254,26 @@ parameters taken from the mmkin object are used</p></td> <span class='no'>f</span> <span class='kw'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span>(<span class='st'>"SFO"</span>, <span class='no'>ds</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fl'>1</span>) <span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>nlme</span>) <span class='no'>f_nlme</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f</span>) -<span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f</span>, <span class='kw'>random</span> <span class='kw'>=</span> <span class='no'>parent_0</span> ~ <span class='fl'>1</span>)</div><div class='output co'>#> Nonlinear mixed-effects model fit by maximum likelihood +<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>f_nlme</span>)</div><div class='output co'>#> Nonlinear mixed-effects model fit by maximum likelihood #> Model: value ~ deg_func(name, time, parent_0, log_k_parent_sink) -#> Data: structure(list(ds = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("1", "2", "3", "4", "5"), class = c("ordered", "factor")), name = c("parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent"), time = c(0, 0, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 0, 0, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 0, 0, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120), value = c(97.2, 96.4, 71.1, 69.2, 58.1, 56.6, 44.4, 43.4, 33.3, 29.2, 17.6, 18, 10.5, 9.3, 4.5, 4.7, 3, 3.4, 2.3, 2.7, 93.6, 92.3, 87, 82.2, 74, 73.9, 64.2, 69.5, 54, 54.6, 41.1, 38.4, 32.5, 35.5, 28.1, 29, 26.5, 27.6, 91.9, 90.8, 64.9, 66.2, 43.5, 44.1, 18.3, 18.1, 10.2, 10.8, 4.9, 3.3, 1.6, 1.5, 1.1, 0.9, 99.8, 98.3, 77.1, 77.2, 59, 58.1, 27.4, 29.2, 19.1, 29.6, 10.1, 18.2, 4.5, 9.1, 2.3, 2.9, 2, 1.8, 2, 2.2, 96.1, 94.3, 73.9, 73.9, 69.4, 73.1, 65.6, 65.3, 55.9, 54.4, 47, 49.3, 44.7, 46.7, 42.1, 41.3)), row.names = c(NA, -90L), class = c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame"), formula = value ~ time | ds, FUN = function (x) max(x, na.rm = TRUE), order.groups = FALSE) -#> Log-likelihood: -394.4901 +#> Data: "Not shown" +#> Log-likelihood: -307.5269 #> Fixed: list(parent_0 ~ 1, log_k_parent_sink ~ 1) #> parent_0 log_k_parent_sink -#> 73.985522 -3.869079 +#> 85.541149 -3.229596 #> #> Random effects: -#> Formula: parent_0 ~ 1 | ds -#> parent_0 Residual -#> StdDev: 18.6134 18.22029 +#> Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1) +#> Level: ds +#> Structure: Diagonal +#> parent_0 log_k_parent_sink Residual +#> StdDev: 1.30857 1.288591 6.304906 #> #> Number of Observations: 90 -#> Number of Groups: 5 </div><div class='input'><span class='no'>f_nlme</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f</span>, <span class='kw'>start</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent_0</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>log_k_parent_sink</span> <span class='kw'>=</span> <span class='fl'>0.1</span>)) -<span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span>(<span class='no'>f_nlme</span>, <span class='kw'>random</span> <span class='kw'>=</span> <span class='no'>parent_0</span> ~ <span class='fl'>1</span>)</div><div class='output co'>#> Nonlinear mixed-effects model fit by maximum likelihood +#> Number of Groups: 5 </div><div class='input'><span class='no'>f_nlme_2</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f</span>, <span class='kw'>start</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent_0</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>log_k_parent_sink</span> <span class='kw'>=</span> <span class='fl'>0.1</span>)) +<span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span>(<span class='no'>f_nlme_2</span>, <span class='kw'>random</span> <span class='kw'>=</span> <span class='no'>parent_0</span> ~ <span class='fl'>1</span>)</div><div class='output co'>#> Nonlinear mixed-effects model fit by maximum likelihood #> Model: value ~ deg_func(name, time, parent_0, log_k_parent_sink) -#> Data: structure(list(ds = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L), .Label = c("1", "2", "3", "4", "5"), class = c("ordered", "factor")), name = c("parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent", "parent"), time = c(0, 0, 3, 3, 6, 6, 10, 10, 20, 20, 34, 34, 55, 55, 90, 90, 112, 112, 132, 132, 0, 0, 3, 3, 7, 7, 14, 14, 30, 30, 60, 60, 90, 90, 120, 120, 180, 180, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 0, 0, 1, 1, 3, 3, 8, 8, 14, 14, 27, 27, 48, 48, 70, 70, 91, 91, 120, 120, 0, 0, 8, 8, 14, 14, 21, 21, 41, 41, 63, 63, 91, 91, 120, 120), value = c(97.2, 96.4, 71.1, 69.2, 58.1, 56.6, 44.4, 43.4, 33.3, 29.2, 17.6, 18, 10.5, 9.3, 4.5, 4.7, 3, 3.4, 2.3, 2.7, 93.6, 92.3, 87, 82.2, 74, 73.9, 64.2, 69.5, 54, 54.6, 41.1, 38.4, 32.5, 35.5, 28.1, 29, 26.5, 27.6, 91.9, 90.8, 64.9, 66.2, 43.5, 44.1, 18.3, 18.1, 10.2, 10.8, 4.9, 3.3, 1.6, 1.5, 1.1, 0.9, 99.8, 98.3, 77.1, 77.2, 59, 58.1, 27.4, 29.2, 19.1, 29.6, 10.1, 18.2, 4.5, 9.1, 2.3, 2.9, 2, 1.8, 2, 2.2, 96.1, 94.3, 73.9, 73.9, 69.4, 73.1, 65.6, 65.3, 55.9, 54.4, 47, 49.3, 44.7, 46.7, 42.1, 41.3)), row.names = c(NA, -90L), class = c("nfnGroupedData", "nfGroupedData", "groupedData", "data.frame"), formula = value ~ time | ds, FUN = function (x) max(x, na.rm = TRUE), order.groups = FALSE) +#> Data: "Not shown" #> Log-likelihood: -404.3729 #> Fixed: list(parent_0 ~ 1, log_k_parent_sink ~ 1) #> parent_0 log_k_parent_sink @@ -265,7 +285,133 @@ parameters taken from the mmkin object are used</p></td> #> StdDev: 0.002416792 21.63027 #> #> Number of Observations: 90 -#> Number of Groups: 5 </div></pre> +#> Number of Groups: 5 </div><div class='input'><span class='co'># \dontrun{</span> + <span class='co'># Test on some real data</span> + <span class='no'>ds_2</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span>(<span class='no'>experimental_data_for_UBA_2019</span>[<span class='fl'>6</span>:<span class='fl'>10</span>], + <span class='kw'>function</span>(<span class='no'>x</span>) <span class='no'>x</span>$<span class='no'>data</span>[<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"name"</span>, <span class='st'>"time"</span>, <span class='st'>"value"</span>)]) + <span class='no'>m_sfo_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"A1"</span>), + <span class='kw'>A1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"min"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) + <span class='no'>m_sfo_sfo_ff</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"A1"</span>), + <span class='kw'>A1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) + <span class='no'>m_fomc_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"FOMC"</span>, <span class='st'>"A1"</span>), + <span class='kw'>A1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) + <span class='no'>m_dfop_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"DFOP"</span>, <span class='st'>"A1"</span>), + <span class='kw'>A1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) + + <span class='no'>f_2</span> <span class='kw'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='st'>"SFO-SFO"</span> <span class='kw'>=</span> <span class='no'>m_sfo_sfo</span>, + <span class='st'>"SFO-SFO-ff"</span> <span class='kw'>=</span> <span class='no'>m_sfo_sfo_ff</span>, + <span class='st'>"FOMC-SFO"</span> <span class='kw'>=</span> <span class='no'>m_fomc_sfo</span>, + <span class='st'>"DFOP-SFO"</span> <span class='kw'>=</span> <span class='no'>m_dfop_sfo</span>), + <span class='no'>ds_2</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) + <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_2</span>[<span class='st'>"SFO-SFO"</span>, <span class='fl'>3</span>:<span class='fl'>4</span>]) <span class='co'># Separate fits for datasets 3 and 4</span></div><div class='img'><img src='nlme.mmkin-1.png' alt='' width='700' height='433' /></div><div class='input'> + <span class='no'>f_nlme_sfo_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f_2</span>[<span class='st'>"SFO-SFO"</span>, ]) + <span class='co'># plot(f_nlme_sfo_sfo) # not feasible with pkgdown figures</span> + <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_nlme_sfo_sfo</span>, <span class='fl'>3</span>:<span class='fl'>4</span>) <span class='co'># Global mixed model: Fits for datasets 3 and 4</span></div><div class='img'><img src='nlme.mmkin-2.png' alt='' width='700' height='433' /></div><div class='input'> + <span class='co'># With formation fractions</span> + <span class='no'>f_nlme_sfo_sfo_ff</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f_2</span>[<span class='st'>"SFO-SFO-ff"</span>, ]) + <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_nlme_sfo_sfo_ff</span>, <span class='fl'>3</span>:<span class='fl'>4</span>) <span class='co'># chi2 different due to different df attribution</span></div><div class='img'><img src='nlme.mmkin-3.png' alt='' width='700' height='433' /></div><div class='input'> + <span class='co'># For more parameters, we need to increase pnlsMaxIter and the tolerance</span> + <span class='co'># to get convergence</span> + <span class='no'>f_nlme_fomc_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f_2</span>[<span class='st'>"FOMC-SFO"</span>, ], + <span class='kw'>control</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>pnlsMaxIter</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>tolerance</span> <span class='kw'>=</span> <span class='fl'>1e-4</span>), <span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#> +#> **Iteration 1 +#> LME step: Loglik: -394.1603, nlminb iterations: 2 +#> reStruct parameters: +#> ds1 ds2 ds3 ds4 ds5 +#> -0.2079984 0.8563873 1.7454146 1.0917723 1.2756924 +#> Beginning PNLS step: .. completed fit_nlme() step. +#> PNLS step: RSS = 643.8786 +#> fixed effects: 94.17379 -5.473199 -0.6970239 -0.2025094 2.103883 +#> iterations: 100 +#> Convergence crit. (must all become <= tolerance = 0.0001): +#> fixed reStruct +#> 0.7865373 0.1448077 +#> +#> **Iteration 2 +#> LME step: Loglik: -396.3824, nlminb iterations: 7 +#> reStruct parameters: +#> ds1 ds2 ds3 ds4 ds5 +#> -1.712408e-01 -2.680989e-05 1.842119e+00 1.073975e+00 1.322924e+00 +#> Beginning PNLS step: .. completed fit_nlme() step. +#> PNLS step: RSS = 643.8022 +#> fixed effects: 94.17385 -5.473491 -0.6970405 -0.202514 2.103871 +#> iterations: 100 +#> Convergence crit. (must all become <= tolerance = 0.0001): +#> fixed reStruct +#> 5.341904e-05 1.227073e-03 +#> +#> **Iteration 3 +#> LME step: Loglik: -396.3825, nlminb iterations: 7 +#> reStruct parameters: +#> ds1 ds2 ds3 ds4 ds5 +#> -0.1712484347 -0.0001513555 1.8420964843 1.0739800649 1.3229176990 +#> Beginning PNLS step: .. completed fit_nlme() step. +#> PNLS step: RSS = 643.7947 +#> fixed effects: 94.17386 -5.473522 -0.6970423 -0.2025142 2.10387 +#> iterations: 100 +#> Convergence crit. (must all become <= tolerance = 0.0001): +#> fixed reStruct +#> 5.568186e-06 1.276609e-04 +#> +#> **Iteration 4 +#> LME step: Loglik: -396.3825, nlminb iterations: 7 +#> reStruct parameters: +#> ds1 ds2 ds3 ds4 ds5 +#> -0.171251200 -0.000164506 1.842095097 1.073980200 1.322916184 +#> Beginning PNLS step: .. completed fit_nlme() step. +#> PNLS step: RSS = 643.7934 +#> fixed effects: 94.17386 -5.473526 -0.6970426 -0.2025146 2.103869 +#> iterations: 100 +#> Convergence crit. (must all become <= tolerance = 0.0001): +#> fixed reStruct +#> 2.332100e-06 1.979007e-05 </div><div class='input'> <span class='no'>f_nlme_dfop_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f_2</span>[<span class='st'>"DFOP-SFO"</span>, ], + <span class='kw'>control</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>pnlsMaxIter</span> <span class='kw'>=</span> <span class='fl'>120</span>, <span class='kw'>tolerance</span> <span class='kw'>=</span> <span class='fl'>5e-4</span>), <span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#> +#> **Iteration 1 +#> LME step: Loglik: -404.9591, nlminb iterations: 1 +#> reStruct parameters: +#> ds1 ds2 ds3 ds4 ds5 ds6 +#> -0.4114594 0.9798456 1.6990016 0.7293119 0.3353829 1.7112922 +#> Beginning PNLS step: .. completed fit_nlme() step. +#> PNLS step: RSS = 630.391 +#> fixed effects: 93.82265 -5.455841 -0.6788837 -1.862191 -4.199654 0.05531046 +#> iterations: 120 +#> Convergence crit. (must all become <= tolerance = 0.0005): +#> fixed reStruct +#> 0.7872619 0.5811683 +#> +#> **Iteration 2 +#> LME step: Loglik: -407.7755, nlminb iterations: 11 +#> reStruct parameters: +#> ds1 ds2 ds3 ds4 ds5 ds6 +#> -0.371222832 0.003084754 1.789952290 0.724634064 0.301559136 1.754244638 +#> Beginning PNLS step: .. completed fit_nlme() step. +#> PNLS step: RSS = 630.359 +#> fixed effects: 93.82269 -5.456014 -0.6788967 -1.862202 -4.199678 0.05534118 +#> iterations: 120 +#> Convergence crit. (must all become <= tolerance = 0.0005): +#> fixed reStruct +#> 0.0005550885 0.0007749418 +#> +#> **Iteration 3 +#> LME step: Loglik: -407.7756, nlminb iterations: 11 +#> reStruct parameters: +#> ds1 ds2 ds3 ds4 ds5 ds6 +#> -0.371217033 0.003064156 1.789935045 0.724683005 0.301622307 1.754234135 +#> Beginning PNLS step: .. completed fit_nlme() step. +#> PNLS step: RSS = 630.358 +#> fixed effects: 93.82269 -5.456017 -0.6788969 -1.862197 -4.199677 0.05532978 +#> iterations: 120 +#> Convergence crit. (must all become <= tolerance = 0.0005): +#> fixed reStruct +#> 2.059533e-04 4.860085e-05 </div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_2</span>[<span class='st'>"FOMC-SFO"</span>, <span class='fl'>3</span>:<span class='fl'>4</span>])</div><div class='img'><img src='nlme.mmkin-4.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_nlme_fomc_sfo</span>, <span class='fl'>3</span>:<span class='fl'>4</span>)</div><div class='img'><img src='nlme.mmkin-5.png' alt='' width='700' height='433' /></div><div class='input'> + <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_2</span>[<span class='st'>"DFOP-SFO"</span>, <span class='fl'>3</span>:<span class='fl'>4</span>])</div><div class='img'><img src='nlme.mmkin-6.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_nlme_dfop_sfo</span>, <span class='fl'>3</span>:<span class='fl'>4</span>)</div><div class='img'><img src='nlme.mmkin-7.png' alt='' width='700' height='433' /></div><div class='input'> + <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span>(<span class='no'>f_nlme_dfop_sfo</span>, <span class='no'>f_nlme_fomc_sfo</span>, <span class='no'>f_nlme_sfo_sfo</span>)</div><div class='output co'>#> Model df AIC BIC logLik Test L.Ratio p-value +#> f_nlme_dfop_sfo 1 13 843.8541 884.6194 -408.9270 +#> f_nlme_fomc_sfo 2 11 818.5149 853.0087 -398.2575 1 vs 2 21.33913 <.0001 +#> f_nlme_sfo_sfo 3 9 1085.1821 1113.4042 -533.5910 2 vs 3 270.66712 <.0001</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span>(<span class='no'>f_nlme_dfop_sfo</span>, <span class='no'>f_nlme_sfo_sfo</span>) <span class='co'># if we ignore FOMC</span></div><div class='output co'>#> Model df AIC BIC logLik Test L.Ratio p-value +#> f_nlme_dfop_sfo 1 13 843.8541 884.6194 -408.927 +#> f_nlme_sfo_sfo 2 9 1085.1821 1113.4042 -533.591 1 vs 2 249.328 <.0001</div><div class='input'># } +</div></pre> </div> <div class="col-md-3 hidden-xs hidden-sm" id="sidebar"> <h2>Contents</h2> |