diff options
| -rw-r--r-- | vignettes/FOCUS_L.html | 208 | ||||
| -rw-r--r-- | vignettes/FOCUS_Z.pdf | bin | 220177 -> 213325 bytes | |||
| -rw-r--r-- | vignettes/mkin.pdf | bin | 160326 -> 160333 bytes |
3 files changed, 111 insertions, 97 deletions
diff --git a/vignettes/FOCUS_L.html b/vignettes/FOCUS_L.html index 2dd186de..c0430358 100644 --- a/vignettes/FOCUS_L.html +++ b/vignettes/FOCUS_L.html @@ -5,6 +5,18 @@ <title>Example evaluation of FOCUS Laboratory Data L1 to L3</title> +<script type="text/javascript"> +window.onload = function() { + var imgs = document.getElementsByTagName('img'), i, img; + for (i = 0; i < imgs.length; i++) { + img = imgs[i]; + // center an image if it is the only element of its parent + if (img.parentElement.childElementCount === 1) + img.parentElement.style.textAlign = 'center'; + } +}; +</script> + <!-- Styles for R syntax highlighter --> <style type="text/css"> pre .operator, @@ -13,19 +25,21 @@ } pre .literal { - color: rgb(88, 72, 246) + color: #990073 } pre .number { - color: rgb(0, 0, 205); + color: #099; } pre .comment { - color: rgb(76, 136, 107); + color: #998; + font-style: italic } pre .keyword { - color: rgb(0, 0, 255); + color: #900; + font-weight: bold } pre .identifier { @@ -33,7 +47,7 @@ } pre .string { - color: rgb(3, 106, 7); + color: #d14; } </style> @@ -43,64 +57,71 @@ var hljs=new function(){function m(p){return p.replace(/&/gm,"&").replace(/< hljs.initHighlightingOnLoad(); </script> -<!-- MathJax scripts --> -<script type="text/javascript" src="https://c328740.ssl.cf1.rackcdn.com/mathjax/2.0-latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML"> -</script> <style type="text/css"> body, td { font-family: sans-serif; background-color: white; - font-size: 12px; - margin: 8px; + font-size: 13px; +} + +body { + max-width: 800px; + margin: auto; + padding: 1em; + line-height: 20px; } tt, code, pre { font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace; } -h1 { - font-size:2.2em; +h1 { + font-size:2.2em; } -h2 { - font-size:1.8em; +h2 { + font-size:1.8em; } -h3 { - font-size:1.4em; +h3 { + font-size:1.4em; } -h4 { - font-size:1.0em; +h4 { + font-size:1.0em; } -h5 { - font-size:0.9em; +h5 { + font-size:0.9em; } -h6 { - font-size:0.8em; +h6 { + font-size:0.8em; } a:visited { color: rgb(50%, 0%, 50%); } -pre { - margin-top: 0; - max-width: 95%; - border: 1px solid #ccc; - white-space: pre-wrap; +pre, img { + max-width: 100%; +} +pre { + overflow-x: auto; } - pre code { display: block; padding: 0.5em; } -code.r, code.cpp { - background-color: #F8F8F8; +code { + font-size: 92%; + border: 1px solid #ccc; +} + +code[class] { + background-color: #F8F8F8; } table, td, th { @@ -123,54 +144,54 @@ hr { } @media print { - * { - background: transparent !important; - color: black !important; - filter:none !important; - -ms-filter: none !important; + * { + background: transparent !important; + color: black !important; + filter:none !important; + -ms-filter: none !important; } - body { - font-size:12pt; - max-width:100%; + body { + font-size:12pt; + max-width:100%; } - - a, a:visited { - text-decoration: underline; + + a, a:visited { + text-decoration: underline; } - hr { + hr { visibility: hidden; page-break-before: always; } - pre, blockquote { - padding-right: 1em; - page-break-inside: avoid; + pre, blockquote { + padding-right: 1em; + page-break-inside: avoid; } - tr, img { - page-break-inside: avoid; + tr, img { + page-break-inside: avoid; } - img { - max-width: 100% !important; + img { + max-width: 100% !important; } - @page :left { - margin: 15mm 20mm 15mm 10mm; + @page :left { + margin: 15mm 20mm 15mm 10mm; } - - @page :right { - margin: 15mm 10mm 15mm 20mm; + + @page :right { + margin: 15mm 10mm 15mm 20mm; } - p, h2, h3 { - orphans: 3; widows: 3; + p, h2, h3 { + orphans: 3; widows: 3; } - h2, h3 { - page-break-after: avoid; + h2, h3 { + page-break-after: avoid; } } </style> @@ -193,13 +214,7 @@ hr { report, p. 284:</p> <pre><code class="r">library("mkin") -</code></pre> - -<pre><code>## Loading required package: minpack.lm -## Loading required package: rootSolve -</code></pre> - -<pre><code class="r">FOCUS_2006_L1 = data.frame( +FOCUS_2006_L1 = data.frame( t = rep(c(0, 1, 2, 3, 5, 7, 14, 21, 30), each = 2), parent = c(88.3, 91.4, 85.6, 84.5, 78.9, 77.6, 72.0, 71.9, 50.3, 59.4, 47.0, 45.1, @@ -223,8 +238,8 @@ summary(m.L1.SFO) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:14 2014 -## Date of summary: Mon Aug 25 10:34:14 2014 +## Date of fit: Sat Oct 11 11:06:43 2014 +## Date of summary: Sat Oct 11 11:06:43 2014 ## ## Equations: ## d_parent = - k_parent_sink * parent @@ -308,9 +323,8 @@ summary(m.L1.SFO) <pre><code class="r">plot(m.L1.SFO) </code></pre> -<p><img src="data:image/png;base64,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alt="plot of chunk unnamed-chunk-4"/> </p> - -<p>The residual plot can be easily obtained by</p> +<p><img src="data:image/png;base64,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" alt="plot of chunk unnamed-chunk-4"/> +The residual plot can be easily obtained by</p> <pre><code class="r">mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time") </code></pre> @@ -326,15 +340,15 @@ summary(m.L1.FOMC, data = FALSE) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:17 2014 -## Date of summary: Mon Aug 25 10:34:17 2014 +## Date of fit: Sat Oct 11 11:06:44 2014 +## Date of summary: Sat Oct 11 11:06:44 2014 ## ## Equations: ## d_parent = - (alpha/beta) * ((time/beta) + 1)^-1 * parent ## ## Model predictions using solution type analytical ## -## Fitted with method Marq using 53 model solutions performed in 0.3 s +## Fitted with method Marq using 53 model solutions performed in 0.314 s ## ## Weighting: none ## @@ -420,15 +434,15 @@ summary(m.L2.SFO) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:17 2014 -## Date of summary: Mon Aug 25 10:34:17 2014 +## Date of fit: Sat Oct 11 11:06:44 2014 +## Date of summary: Sat Oct 11 11:06:44 2014 ## ## Equations: ## d_parent = - k_parent_sink * parent ## ## Model predictions using solution type analytical ## -## Fitted with method Marq using 29 model solutions performed in 0.184 s +## Fitted with method Marq using 29 model solutions performed in 0.173 s ## ## Weighting: none ## @@ -530,15 +544,15 @@ mkinresplot(m.L2.FOMC) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:17 2014 -## Date of summary: Mon Aug 25 10:34:17 2014 +## Date of fit: Sat Oct 11 11:06:46 2014 +## Date of summary: Sat Oct 11 11:06:47 2014 ## ## Equations: ## d_parent = - (alpha/beta) * ((time/beta) + 1)^-1 * parent ## ## Model predictions using solution type analytical ## -## Fitted with method Marq using 35 model solutions performed in 0.2 s +## Fitted with method Marq using 35 model solutions performed in 0.206 s ## ## Weighting: none ## @@ -616,8 +630,8 @@ plot(m.L2.DFOP) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:18 2014 -## Date of summary: Mon Aug 25 10:34:18 2014 +## Date of fit: Sat Oct 11 11:06:47 2014 +## Date of summary: Sat Oct 11 11:06:47 2014 ## ## Equations: ## d_parent = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -626,7 +640,7 @@ plot(m.L2.DFOP) ## ## Model predictions using solution type analytical ## -## Fitted with method Marq using 43 model solutions performed in 0.26 s +## Fitted with method Marq using 43 model solutions performed in 0.265 s ## ## Weighting: none ## @@ -705,15 +719,15 @@ plot(m.L3.SFO) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:18 2014 -## Date of summary: Mon Aug 25 10:34:18 2014 +## Date of fit: Sat Oct 11 11:06:48 2014 +## Date of summary: Sat Oct 11 11:06:48 2014 ## ## Equations: ## d_parent = - k_parent_sink * parent ## ## Model predictions using solution type analytical ## -## Fitted with method Marq using 44 model solutions performed in 0.252 s +## Fitted with method Marq using 44 model solutions performed in 0.261 s ## ## Weighting: none ## @@ -791,15 +805,15 @@ plot(m.L3.FOMC) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:19 2014 -## Date of summary: Mon Aug 25 10:34:19 2014 +## Date of fit: Sat Oct 11 11:06:48 2014 +## Date of summary: Sat Oct 11 11:06:48 2014 ## ## Equations: ## d_parent = - (alpha/beta) * ((time/beta) + 1)^-1 * parent ## ## Model predictions using solution type analytical ## -## Fitted with method Marq using 26 model solutions performed in 0.148 s +## Fitted with method Marq using 26 model solutions performed in 0.159 s ## ## Weighting: none ## @@ -864,8 +878,8 @@ plot(m.L3.DFOP) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:19 2014 -## Date of summary: Mon Aug 25 10:34:19 2014 +## Date of fit: Sat Oct 11 11:06:50 2014 +## Date of summary: Sat Oct 11 11:06:50 2014 ## ## Equations: ## d_parent = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -874,7 +888,7 @@ plot(m.L3.DFOP) ## ## Model predictions using solution type analytical ## -## Fitted with method Marq using 37 model solutions performed in 0.236 s +## Fitted with method Marq using 37 model solutions performed in 0.225 s ## ## Weighting: none ## @@ -962,15 +976,15 @@ plot(m.L4.SFO) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:19 2014 -## Date of summary: Mon Aug 25 10:34:19 2014 +## Date of fit: Sat Oct 11 11:06:51 2014 +## Date of summary: Sat Oct 11 11:06:51 2014 ## ## Equations: ## d_parent = - k_parent_sink * parent ## ## Model predictions using solution type analytical ## -## Fitted with method Marq using 20 model solutions performed in 0.123 s +## Fitted with method Marq using 20 model solutions performed in 0.119 s ## ## Weighting: none ## @@ -1037,15 +1051,15 @@ plot(m.L4.FOMC) <pre><code>## mkin version: 0.9.33 ## R version: 3.1.1 -## Date of fit: Mon Aug 25 10:34:20 2014 -## Date of summary: Mon Aug 25 10:34:20 2014 +## Date of fit: Sat Oct 11 11:06:51 2014 +## Date of summary: Sat Oct 11 11:06:51 2014 ## ## Equations: ## d_parent = - (alpha/beta) * ((time/beta) + 1)^-1 * parent ## ## Model predictions using solution type analytical ## -## Fitted with method Marq using 48 model solutions performed in 0.281 s +## Fitted with method Marq using 48 model solutions performed in 0.283 s ## ## Weighting: none ## diff --git a/vignettes/FOCUS_Z.pdf b/vignettes/FOCUS_Z.pdf Binary files differindex ca6d2506..426aa0df 100644 --- a/vignettes/FOCUS_Z.pdf +++ b/vignettes/FOCUS_Z.pdf diff --git a/vignettes/mkin.pdf b/vignettes/mkin.pdf Binary files differindex 0cc413a1..83182e65 100644 --- a/vignettes/mkin.pdf +++ b/vignettes/mkin.pdf |