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author | Johannes Ranke <jranke@uni-bremen.de> | 2019-11-04 17:21:04 +0100 |
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committer | Johannes Ranke <jranke@uni-bremen.de> | 2019-11-04 17:29:48 +0100 |
commit | 31fd7412f46c9715962763d435cb0060ea420752 (patch) | |
tree | 771183a2c729131e7364f0a41dae967f73dc150e /docs/reference/confint.mkinfit.html | |
parent | 0220b25f01a4451fa44a7b2f30f5849c4d822a9c (diff) |
Include fixed parameters in model names in lrtest
Diffstat (limited to 'docs/reference/confint.mkinfit.html')
-rw-r--r-- | docs/reference/confint.mkinfit.html | 20 |
1 files changed, 10 insertions, 10 deletions
diff --git a/docs/reference/confint.mkinfit.html b/docs/reference/confint.mkinfit.html index 13662adf..ea69c3bb 100644 --- a/docs/reference/confint.mkinfit.html +++ b/docs/reference/confint.mkinfit.html @@ -40,10 +40,10 @@ 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 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)." /> +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)." /> <meta name="twitter:card" content="summary" /> @@ -144,10 +144,10 @@ and Moolgavkar (1988)." /> 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 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> +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> @@ -254,13 +254,13 @@ On Windows machines, cores > 1 is currently not supported.</p></td> <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 verstrichen -#> 51.341 0.000 51.370 </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> +#> 51.058 0.000 51.088 </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'>#> User System verstrichen -#> 0.001 0.007 11.432 </div><div class='input'><span class='no'>ci_profile</span></div><div class='output co'>#> 2.5% 97.5% +#> 0.005 0.004 11.349 </div><div class='input'><span class='no'>ci_profile</span></div><div class='output co'>#> 2.5% 97.5% #> parent_0 96.456003650 1.027703e+02 #> k_parent_sink 0.040762501 5.549764e-02 #> k_parent_m1 0.046786482 5.500879e-02 |