-
Notifications
You must be signed in to change notification settings - Fork 0
/
m4_children_nonlinear.html
158 lines (127 loc) · 8.31 KB
/
m4_children_nonlinear.html
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta charset="utf-8">
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<meta name="generator" content="pandoc" />
<title> Children Nonlinear</title>
<script src="library/jquery-1.11.3/jquery.min.js"></script>
<meta name="viewport" content="width=device-width, initial-scale=1" />
<link href="library/bootstrap-3.3.5/css/paper.min.css" rel="stylesheet" />
<script src="library/bootstrap-3.3.5/js/bootstrap.min.js"></script>
<script src="library/bootstrap-3.3.5/shim/html5shiv.min.js"></script>
<script src="library/bootstrap-3.3.5/shim/respond.min.js"></script>
<script src="library/navigation-1.1/tabsets.js"></script>
<style type="text/css">code{white-space: pre;}</style>
<style type="text/css">
div.sourceCode { overflow-x: auto; }
table.sourceCode, tr.sourceCode, td.lineNumbers, td.sourceCode {
margin: 0; padding: 0; vertical-align: baseline; border: none; }
table.sourceCode { width: 100%; line-height: 100%; }
td.lineNumbers { text-align: right; padding-right: 4px; padding-left: 4px; color: #aaaaaa; border-right: 1px solid #aaaaaa; }
td.sourceCode { padding-left: 5px; }
code > span.kw { color: #007020; font-weight: bold; } /* Keyword */
code > span.dt { color: #902000; } /* DataType */
code > span.dv { color: #40a070; } /* DecVal */
code > span.bn { color: #40a070; } /* BaseN */
code > span.fl { color: #40a070; } /* Float */
code > span.ch { color: #4070a0; } /* Char */
code > span.st { color: #4070a0; } /* String */
code > span.co { color: #60a0b0; font-style: italic; } /* Comment */
code > span.ot { color: #007020; } /* Other */
code > span.al { color: #ff0000; font-weight: bold; } /* Alert */
code > span.fu { color: #06287e; } /* Function */
code > span.er { color: #ff0000; font-weight: bold; } /* Error */
code > span.wa { color: #60a0b0; font-weight: bold; font-style: italic; } /* Warning */
code > span.cn { color: #880000; } /* Constant */
code > span.sc { color: #4070a0; } /* SpecialChar */
code > span.vs { color: #4070a0; } /* VerbatimString */
code > span.ss { color: #bb6688; } /* SpecialString */
code > span.im { } /* Import */
code > span.va { color: #19177c; } /* Variable */
code > span.cf { color: #007020; font-weight: bold; } /* ControlFlow */
code > span.op { color: #666666; } /* Operator */
code > span.bu { } /* BuiltIn */
code > span.ex { } /* Extension */
code > span.pp { color: #bc7a00; } /* Preprocessor */
code > span.at { color: #7d9029; } /* Attribute */
code > span.do { color: #ba2121; font-style: italic; } /* Documentation */
code > span.an { color: #60a0b0; font-weight: bold; font-style: italic; } /* Annotation */
code > span.cv { color: #60a0b0; font-weight: bold; font-style: italic; } /* CommentVar */
code > span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Information */
</style>
<style type="text/css">
pre:not([class]) {
background-color: white;
}
</style>
<style type = "text/css">
.main-container {
max-width: 940px;
margin-left: auto;
margin-right: auto;
}
code {
color: inherit;
background-color: rgba(0, 0, 0, 0.04);
}
img {
max-width:100%;
height: auto;
}
</style>
</head>
<body>
<div class="container-fluid main-container">
<div class="row">
<div class="col-md-2" style="border-top:solid #E2A674 20px"></div>
<div class="col-md-2 rpqa" style="border-top:solid #9F3B2B 20px"></div>
<div class="col-md-4" style="background:black;text-align:center"><a href="index.html" style="color:white"><i class="glyphicon glyphicon-th-list"></i> Back to index</a></div>
<div class="col-md-2 hist_sweden" style="border-top:solid #21523B 20px"></div>
<div class="col-md-2 mod_sweden" style="border-top:solid #8A846C 20px"></div>
</div>
</div>
<div class="container-fluid main-container">
<div id="run-model-on-cluster" class="section level1">
<h1>Run model on cluster</h1>
<p>this script runs a model on our scientific computing cluster</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(dplyr); <span class="kw">library</span>(brms)
<span class="kw">setwd</span>(<span class="st">"/usr/users/rarslan/updated_data/"</span>)
args =<span class="st"> </span><span class="kw">commandArgs</span>()
dataset =<span class="st"> </span>args[<span class="dv">6</span>]
uptobyear =<span class="st"> </span>args[<span class="dv">7</span>]
model_formula =<span class="st"> </span>children ~<span class="st"> </span><span class="kw">s</span>(paternalage) +<span class="st"> </span>birth_cohort +<span class="st"> </span>male +<span class="st"> </span>maternalage.factor +<span class="st"> </span>paternalage.mean +<span class="st"> </span>paternal_loss +<span class="st"> </span>maternal_loss +<span class="st"> </span>older_siblings +<span class="st"> </span>nr.siblings +<span class="st"> </span>last_born +<span class="st"> </span>(<span class="dv">1</span> |<span class="st"> </span>idParents)
if (dataset ==<span class="st"> "swed"</span>) {
<span class="kw">load</span>(<span class="st">"swed1.rdata"</span>)
model_prior =<span class="st"> </span><span class="kw">c</span>(<span class="kw">set_prior</span>(<span class="st">"normal(0,5)"</span>, <span class="dt">class =</span> <span class="st">"b"</span>),
<span class="kw">set_prior</span>(<span class="st">"student_t(3, 0, 5)"</span>, <span class="dt">class =</span> <span class="st">"sd"</span>))
model_family =<span class="st"> </span><span class="kw">poisson</span>()
} else {
<span class="kw">load</span>(<span class="kw">paste0</span>(dataset, <span class="st">".rdata"</span>))
model_prior =<span class="st"> </span><span class="kw">c</span>(<span class="kw">set_prior</span>(<span class="st">"normal(0,5)"</span>, <span class="dt">class =</span> <span class="st">"b"</span>),
<span class="kw">set_prior</span>(<span class="st">"normal(0,5)"</span>, <span class="dt">class =</span> <span class="st">"b"</span>, <span class="dt">nlpar =</span> <span class="st">"hu"</span>),
<span class="kw">set_prior</span>(<span class="st">"student_t(3, 0, 5)"</span>, <span class="dt">class =</span> <span class="st">"sd"</span>))
model_formula_hu =<span class="st"> </span><span class="kw">update</span>(model_formula, hu ~<span class="st"> </span>. )
model_formula =<span class="st"> </span><span class="kw">bf</span>(model_formula, model_formula_hu)
model_family =<span class="st"> </span><span class="kw">hurdle_poisson</span>()
}
model_data =<span class="st"> </span><span class="kw">get</span>(<span class="kw">paste0</span>(dataset, <span class="st">".1"</span>)) %>%<span class="st"> </span>tbl_df %>%<span class="st"> </span>
<span class="st"> </span><span class="kw">filter</span>(byear <<span class="st"> </span>uptobyear) %>%<span class="st"> </span>
<span class="st"> </span><span class="kw">select</span>(children, birth_cohort, male, maternalage.factor, paternalage.mean, paternalage, paternal_loss, maternal_loss, older_siblings, nr.siblings, last_born, idParents) %>%<span class="st"> </span>
<span class="st"> </span><span class="kw">na.omit</span>()
model =<span class="st"> </span><span class="kw">brm</span>( model_formula,
<span class="dt">prior =</span> model_prior,
<span class="dt">family =</span> model_family, <span class="dt">data =</span> model_data,
<span class="dt">chains =</span> <span class="dv">6</span>, <span class="dt">iter =</span> <span class="dv">800</span>, <span class="dt">warmup =</span> <span class="dv">300</span>, <span class="dt">cores =</span> <span class="dv">6</span>, <span class="dt">ranef =</span> <span class="ot">TRUE</span>)
<span class="kw">summary</span>(model)
<span class="kw">saveRDS</span>(model,<span class="dt">file =</span> <span class="kw">paste0</span>(<span class="st">"coefs/"</span>, dataset, <span class="st">"/m4_children_nonlinear.rds"</span>))</code></pre></div>
</div>
</div>
<script>
// add bootstrap table styles to pandoc tables
$(document).ready(function () {
$('tr.header').parent('thead').parent('table').addClass('table table-condensed');
});
</script>
</body>
</html>