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| author | Johannes Ranke <jranke@uni-bremen.de> | 2020-05-27 06:06:08 +0200 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2020-05-27 06:06:08 +0200 |
| commit | a77a10ea6c607346778ba0700b3b66ac393101a2 (patch) | |
| tree | e91f627fba0580ef237ecbc8f24d6294a59597d3 /docs/dev/reference/confint.mkinfit.html | |
| parent | 675a733fa2acc08daabb9b8b571c7d658f281f73 (diff) | |
Create up to date pkgdown docs in development mode
Diffstat (limited to 'docs/dev/reference/confint.mkinfit.html')
| -rw-r--r-- | docs/dev/reference/confint.mkinfit.html | 419 |
1 files changed, 419 insertions, 0 deletions
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The 'profile' method uses two nested optimisations and can take a +very long time, even if parallelized by specifying 'cores' on unixoid +platforms. The speed of the method could likely be improved by using the +method of Venzon and Moolgavkar (1988)." /> + + +<meta name="robots" content="noindex"> + +<!-- mathjax --> +<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script> +<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script> + +<!--[if lt IE 9]> +<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script> +<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script> +<![endif]--> + + + + </head> + + <body data-spy="scroll" data-target="#toc"> + <div class="container template-reference-topic"> + <header> + <div class="navbar navbar-default navbar-fixed-top" role="navigation"> + <div class="container"> + <div class="navbar-header"> + <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar" aria-expanded="false"> + <span class="sr-only">Toggle navigation</span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + <span class="icon-bar"></span> + </button> + <span class="navbar-brand"> + <a class="navbar-link" href="../index.html">mkin</a> + <span class="version label label-danger" data-toggle="tooltip" data-placement="bottom" title="In-development version">0.9.50.3</span> + </span> + </div> + + <div id="navbar" class="navbar-collapse collapse"> + <ul class="nav navbar-nav"> + <li> + <a href="../reference/index.html">Functions and data</a> +</li> +<li class="dropdown"> + <a href="#" class="dropdown-toggle" data-toggle="dropdown" role="button" aria-expanded="false"> + Articles + + <span class="caret"></span> + </a> + <ul class="dropdown-menu" role="menu"> + <li> + <a href="../articles/mkin.html">Introduction to mkin</a> + </li> + <li> + <a href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a> + </li> + <li> + <a href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a> + </li> + <li> + <a href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a> + </li> + <li> + <a href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a> + </li> + <li> + <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a> + </li> + <li> + <a href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a> + </li> + <li> + <a href="../articles/web_only/benchmarks.html">Some benchmark timings</a> + </li> + </ul> +</li> +<li> + <a href="../news/index.html">News</a> +</li> + </ul> + <ul class="nav navbar-nav navbar-right"> + <li> + <a href="http://github.com/jranke/mkin/"> + <span class="fab fa fab fa-github fa-lg"></span> + + </a> +</li> + </ul> + + </div><!--/.nav-collapse --> + </div><!--/.container --> +</div><!--/.navbar --> + + + + </header> + +<div class="row"> + <div class="col-md-9 contents"> + <div class="page-header"> + <h1>Confidence intervals for parameters of mkinfit objects</h1> + <small class="dont-index">Source: <a href='http://github.com/jranke/mkin/blob/master/R/confint.mkinfit.R'><code>R/confint.mkinfit.R</code></a></small> + <div class="hidden name"><code>confint.mkinfit.Rd</code></div> + </div> + + <div class="ref-description"> + <p>The default method 'quadratic' is based on the quadratic approximation of +the curvature of the likelihood function at the maximum likelihood parameter +estimates. +The alternative method 'profile' is based on the profile likelihood for each +parameter. The 'profile' method uses two nested optimisations and can take a +very long time, even if parallelized by specifying 'cores' on unixoid +platforms. The speed of the method could likely be improved by using the +method of Venzon and Moolgavkar (1988).</p> + </div> + + <pre class="usage"><span class='co'># S3 method for mkinfit</span> +<span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>( + <span class='no'>object</span>, + <span class='no'>parm</span>, + <span class='kw'>level</span> <span class='kw'>=</span> <span class='fl'>0.95</span>, + <span class='kw'>alpha</span> <span class='kw'>=</span> <span class='fl'>1</span> - <span class='no'>level</span>, + <span class='no'>cutoff</span>, + <span class='kw'>method</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"quadratic"</span>, <span class='st'>"profile"</span>), + <span class='kw'>transformed</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, + <span class='kw'>backtransform</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, + <span class='kw'>cores</span> <span class='kw'>=</span> <span class='kw pkg'>parallel</span><span class='kw ns'>::</span><span class='fu'><a href='https://rdrr.io/r/parallel/detectCores.html'>detectCores</a></span>(), + <span class='kw'>rel_tol</span> <span class='kw'>=</span> <span class='fl'>0.01</span>, + <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, + <span class='no'>...</span> +)</pre> + + <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2> + <table class="ref-arguments"> + <colgroup><col class="name" /><col class="desc" /></colgroup> + <tr> + <th>object</th> + <td><p>An <code><a href='mkinfit.html'>mkinfit</a></code> object</p></td> + </tr> + <tr> + <th>parm</th> + <td><p>A vector of names of the parameters which are to be given +confidence intervals. If missing, all parameters are considered.</p></td> + </tr> + <tr> + <th>level</th> + <td><p>The confidence level required</p></td> + </tr> + <tr> + <th>alpha</th> + <td><p>The allowed error probability, overrides 'level' if specified.</p></td> + </tr> + <tr> + <th>cutoff</th> + <td><p>Possibility to specify an alternative cutoff for the difference +in the log-likelihoods at the confidence boundary. Specifying an explicit +cutoff value overrides arguments 'level' and 'alpha'</p></td> + </tr> + <tr> + <th>method</th> + <td><p>The 'quadratic' method approximates the likelihood function at +the optimised parameters using the second term of the Taylor expansion, +using a second derivative (hessian) contained in the object. +The 'profile' method searches the parameter space for the +cutoff of the confidence intervals by means of a likelihood ratio test.</p></td> + </tr> + <tr> + <th>transformed</th> + <td><p>If the quadratic approximation is used, should it be +applied to the likelihood based on the transformed parameters?</p></td> + </tr> + <tr> + <th>backtransform</th> + <td><p>If we approximate the likelihood in terms of the +transformed parameters, should we backtransform the parameters with +their confidence intervals?</p></td> + </tr> + <tr> + <th>cores</th> + <td><p>The number of cores to be used for multicore processing. +On Windows machines, cores > 1 is currently not supported.</p></td> + </tr> + <tr> + <th>rel_tol</th> + <td><p>If the method is 'profile', what should be the accuracy +of the lower and upper bounds, relative to the estimate obtained from +the quadratic method?</p></td> + </tr> + <tr> + <th>quiet</th> + <td><p>Should we suppress the message "Profiling the likelihood"</p></td> + </tr> + <tr> + <th>...</th> + <td><p>Not used</p></td> + </tr> + </table> + + <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2> + + <p>A matrix with columns giving lower and upper confidence limits for +each parameter.</p> + <h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2> + + <p>Bates DM and Watts GW (1988) Nonlinear regression analysis & its applications</p> +<p>Pawitan Y (2013) In all likelihood - Statistical modelling and +inference using likelihood. Clarendon Press, Oxford.</p> +<p>Venzon DJ and Moolgavkar SH (1988) A Method for Computing +Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37, +87–94.</p> + + <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2> + <pre class="examples"><div class='input'><span class='no'>f</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='st'>"SFO"</span>, <span class='no'>FOCUS_2006_C</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) +<span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"quadratic"</span>)</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 71.8242430 93.1600766 +#> k_parent_sink 0.2109541 0.4440528 +#> sigma 1.9778868 7.3681380</div><div class='input'> +<span class='co'># \dontrun{</span> +<span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"profile"</span>)</div><div class='output co'>#> <span class='message'>Profiling the likelihood</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 73.0641834 92.1392181 +#> k_parent_sink 0.2170293 0.4235348 +#> sigma 3.1307772 8.0628314</div><div class='input'> +<span class='co'># Set the number of cores for the profiling method for further examples</span> +<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/identical.html'>identical</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/Sys.getenv.html'>Sys.getenv</a></span>(<span class='st'>"NOT_CRAN"</span>), <span class='st'>"true"</span>)) { + <span class='no'>n_cores</span> <span class='kw'><-</span> <span class='kw pkg'>parallel</span><span class='kw ns'>::</span><span class='fu'><a href='https://rdrr.io/r/parallel/detectCores.html'>detectCores</a></span>() - <span class='fl'>1</span> +} <span class='kw'>else</span> { + <span class='no'>n_cores</span> <span class='kw'><-</span> <span class='fl'>1</span> +} +<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/Sys.getenv.html'>Sys.getenv</a></span>(<span class='st'>"TRAVIS"</span>) <span class='kw'>!=</span> <span class='st'>""</span>) <span class='no'>n_cores</span> <span class='kw'>=</span> <span class='fl'>1</span> +<span class='kw'>if</span> (<span class='fu'><a href='https://rdrr.io/r/base/Sys.info.html'>Sys.info</a></span>()[<span class='st'>"sysname"</span>] <span class='kw'>==</span> <span class='st'>"Windows"</span>) <span class='no'>n_cores</span> <span class='kw'>=</span> <span class='fl'>1</span> + +<span class='no'>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'>"m1"</span>), <span class='kw'>m1</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'>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'>"m1"</span>), <span class='kw'>m1</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'>f_d_1</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO</span>, <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span>(<span class='no'>FOCUS_2006_D</span>, <span class='no'>value</span> <span class='kw'>!=</span> <span class='fl'>0</span>), <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) +<span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>(<span class='no'>ci_profile</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_d_1</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"profile"</span>, <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>))</div><div class='output co'>#> user system elapsed +#> 3.707 1.077 3.444 </div><div class='input'><span class='co'># Using more cores does not save much time here, as parent_0 takes up most of the time</span> +<span class='co'># If we additionally exclude parent_0 (the confidence of which is often of</span> +<span class='co'># minor interest), we get a nice performance improvement from about 50</span> +<span class='co'># seconds to about 12 seconds if we use at least four cores</span> +<span class='fu'><a href='https://rdrr.io/r/base/system.time.html'>system.time</a></span>(<span class='no'>ci_profile_no_parent_0</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_d_1</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"profile"</span>, + <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"k_parent_sink"</span>, <span class='st'>"k_parent_m1"</span>, <span class='st'>"k_m1_sink"</span>, <span class='st'>"sigma"</span>), <span class='kw'>cores</span> <span class='kw'>=</span> <span class='no'>n_cores</span>))</div><div class='output co'>#> <span class='message'>Profiling the likelihood</span></div><div class='output co'>#> <span class='warning'>Warning: scheduled cores 2, 1, 3 encountered errors in user code, all values of the jobs will be affected</span></div><div class='output co'>#> <span class='error'>Error in dimnames(x) <- dn: length of 'dimnames' [2] not equal to array extent</span></div><div class='output co'>#> <span class='message'>Timing stopped at: 0.011 0.026 0.207</span></div><div class='input'><span class='no'>ci_profile</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.456003640 1.027703e+02 +#> k_parent 0.090911032 1.071578e-01 +#> k_m1 0.003892605 6.702778e-03 +#> f_parent_to_m1 0.471328495 5.611550e-01 +#> sigma 2.535612399 3.985263e+00</div><div class='input'><span class='no'>ci_quadratic_transformed</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_d_1</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"quadratic"</span>) +<span class='no'>ci_quadratic_transformed</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.403839476 1.027931e+02 +#> k_parent 0.090823790 1.072543e-01 +#> k_m1 0.004012216 6.897547e-03 +#> f_parent_to_m1 0.469118713 5.595960e-01 +#> sigma 2.396089689 3.854918e+00</div><div class='input'><span class='no'>ci_quadratic_untransformed</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_d_1</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"quadratic"</span>, <span class='kw'>transformed</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>) +<span class='no'>ci_quadratic_untransformed</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.403839429 1.027931e+02 +#> k_parent 0.090491931 1.069035e-01 +#> k_m1 0.003835483 6.685819e-03 +#> f_parent_to_m1 0.469113364 5.598386e-01 +#> sigma 2.396089689 3.854918e+00</div><div class='input'><span class='co'># Against the expectation based on Bates and Watts (1988), the confidence</span> +<span class='co'># intervals based on the internal parameter transformation are less</span> +<span class='co'># congruent with the likelihood based intervals. Note the superiority of the</span> +<span class='co'># interval based on the untransformed fit for k_m1_sink</span> +<span class='no'>rel_diffs_transformed</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>abs</a></span>((<span class='no'>ci_quadratic_transformed</span> - <span class='no'>ci_profile</span>)/<span class='no'>ci_profile</span>) +<span class='no'>rel_diffs_untransformed</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>abs</a></span>((<span class='no'>ci_quadratic_untransformed</span> - <span class='no'>ci_profile</span>)/<span class='no'>ci_profile</span>) +<span class='no'>rel_diffs_transformed</span> <span class='kw'><</span> <span class='no'>rel_diffs_untransformed</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 TRUE TRUE +#> k_parent TRUE TRUE +#> k_m1 FALSE FALSE +#> f_parent_to_m1 TRUE FALSE +#> sigma FALSE TRUE</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span>(<span class='no'>rel_diffs_transformed</span>, <span class='fl'>3</span>)</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 0.000541 0.000222 +#> k_parent 0.000960 0.000900 +#> k_m1 0.030700 0.029100 +#> f_parent_to_m1 0.004690 0.002780 +#> sigma 0.055000 0.032700</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/Round.html'>signif</a></span>(<span class='no'>rel_diffs_untransformed</span>, <span class='fl'>3</span>)</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 0.000541 0.000222 +#> k_parent 0.004610 0.002370 +#> k_m1 0.014700 0.002530 +#> f_parent_to_m1 0.004700 0.002350 +#> sigma 0.055000 0.032700</div><div class='input'> + +<span class='co'># Investigate a case with formation fractions</span> +<span class='no'>f_d_2</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO.ff</span>, <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span>(<span class='no'>FOCUS_2006_D</span>, <span class='no'>value</span> <span class='kw'>!=</span> <span class='fl'>0</span>), <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) +<span class='no'>ci_profile_ff</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_d_2</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"profile"</span>, <span class='kw'>cores</span> <span class='kw'>=</span> <span class='no'>n_cores</span>)</div><div class='output co'>#> <span class='message'>Profiling the likelihood</span></div><div class='input'><span class='no'>ci_profile_ff</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.456003640 1.027703e+02 +#> k_parent 0.090911032 1.071578e-01 +#> k_m1 0.003892605 6.702778e-03 +#> f_parent_to_m1 0.471328495 5.611550e-01 +#> sigma 2.535612399 3.985263e+00</div><div class='input'><span class='no'>ci_quadratic_transformed_ff</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_d_2</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"quadratic"</span>) +<span class='no'>ci_quadratic_transformed_ff</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.403839476 1.027931e+02 +#> k_parent 0.090823790 1.072543e-01 +#> k_m1 0.004012216 6.897547e-03 +#> f_parent_to_m1 0.469118713 5.595960e-01 +#> sigma 2.396089689 3.854918e+00</div><div class='input'><span class='no'>ci_quadratic_untransformed_ff</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_d_2</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"quadratic"</span>, <span class='kw'>transformed</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>) +<span class='no'>ci_quadratic_untransformed_ff</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 96.403839429 1.027931e+02 +#> k_parent 0.090491931 1.069035e-01 +#> k_m1 0.003835483 6.685819e-03 +#> f_parent_to_m1 0.469113364 5.598386e-01 +#> sigma 2.396089689 3.854918e+00</div><div class='input'><span class='no'>rel_diffs_transformed_ff</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>abs</a></span>((<span class='no'>ci_quadratic_transformed_ff</span> - <span class='no'>ci_profile_ff</span>)/<span class='no'>ci_profile_ff</span>) +<span class='no'>rel_diffs_untransformed_ff</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/MathFun.html'>abs</a></span>((<span class='no'>ci_quadratic_untransformed_ff</span> - <span class='no'>ci_profile_ff</span>)/<span class='no'>ci_profile_ff</span>) +<span class='co'># While the confidence interval for the parent rate constant is closer to</span> +<span class='co'># the profile based interval when using the internal parameter</span> +<span class='co'># transformation, the interval for the metabolite rate constant is 'better</span> +<span class='co'># without internal parameter transformation.</span> +<span class='no'>rel_diffs_transformed_ff</span> <span class='kw'><</span> <span class='no'>rel_diffs_untransformed_ff</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 TRUE TRUE +#> k_parent TRUE TRUE +#> k_m1 FALSE FALSE +#> f_parent_to_m1 TRUE FALSE +#> sigma FALSE TRUE</div><div class='input'><span class='no'>rel_diffs_transformed_ff</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 0.0005408078 0.0002217796 +#> k_parent 0.0009596417 0.0009003876 +#> k_m1 0.0307277372 0.0290579184 +#> f_parent_to_m1 0.0046884131 0.0027782558 +#> sigma 0.0550252516 0.0327066836</div><div class='input'><span class='no'>rel_diffs_untransformed_ff</span></div><div class='output co'>#> 2.5% 97.5% +#> parent_0 0.0005408083 0.000221780 +#> k_parent 0.0046100096 0.002373023 +#> k_m1 0.0146746467 0.002530101 +#> f_parent_to_m1 0.0046997600 0.002346022 +#> sigma 0.0550252516 0.032706684</div><div class='input'> +<span class='co'># The profiling for the following fit does not finish in a reasonable time,</span> +<span class='co'># therefore we use the quadratic approximation</span> +<span class='no'>m_synth_DFOP_par</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='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"M1"</span>, <span class='st'>"M2"</span>)), + <span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), + <span class='kw'>M2</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'>DFOP_par_c</span> <span class='kw'><-</span> <span class='no'>synthetic_data_for_UBA_2014</span><span class='kw'>[[</span><span class='fl'>12</span>]]$<span class='no'>data</span> +<span class='no'>f_tc_2</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>m_synth_DFOP_par</span>, <span class='no'>DFOP_par_c</span>, <span class='kw'>error_model</span> <span class='kw'>=</span> <span class='st'>"tc"</span>, + <span class='kw'>error_model_algorithm</span> <span class='kw'>=</span> <span class='st'>"direct"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#> <span class='warning'>Warning: Optimisation did not converge:</span> +#> <span class='warning'>iteration limit reached without convergence (10)</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_tc_2</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"quadratic"</span>)</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 95.654015524 105.79279749 +#> k_M1 0.037723773 0.04447598 +#> k_M2 0.008586438 0.01078076 +#> f_parent_to_M1 0.230403596 0.61953014 +#> f_parent_to_M2 0.162909765 0.38019017 +#> k1 0.275434628 0.33331386 +#> k2 0.018602188 0.02249211 +#> g 0.675149759 0.73520889 +#> sigma_low 0.251416929 0.84272023 +#> rsd_high 0.040371818 0.07666540</div><div class='input'><span class='fu'><a href='https://rdrr.io/r/stats/confint.html'>confint</a></span>(<span class='no'>f_tc_2</span>, <span class='st'>"parent_0"</span>, <span class='kw'>method</span> <span class='kw'>=</span> <span class='st'>"quadratic"</span>)</div><div class='output co'>#> 2.5% 97.5% +#> parent_0 95.65402 105.7928</div><div class='input'># } +</div></pre> + </div> + <div class="col-md-3 hidden-xs hidden-sm" id="pkgdown-sidebar"> + <nav id="toc" data-toggle="toc" class="sticky-top"> + <h2 data-toc-skip>Contents</h2> + </nav> + </div> +</div> + + + <footer> + <div class="copyright"> + <p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown"> + <p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.5.1.</p> +</div> + + </footer> + </div> + + + + + </body> +</html> + + |