-
Notifications
You must be signed in to change notification settings - Fork 40
/
Lrnr_bayesglm.html
288 lines (233 loc) · 13.4 KB
/
Lrnr_bayesglm.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
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
<!-- Generated by pkgdown: do not edit by hand -->
<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Bayesian Generalized Linear Models — Lrnr_bayesglm • sl3</title>
<!-- jquery -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.4.1/jquery.min.js" integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
<!-- Bootstrap -->
<link href="https://cdnjs.cloudflare.com/ajax/libs/bootswatch/3.4.0/flatly/bootstrap.min.css" rel="stylesheet" crossorigin="anonymous" />
<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.4.1/js/bootstrap.min.js" integrity="sha256-nuL8/2cJ5NDSSwnKD8VqreErSWHtnEP9E7AySL+1ev4=" crossorigin="anonymous"></script>
<!-- bootstrap-toc -->
<link rel="stylesheet" href="../bootstrap-toc.css">
<script src="../bootstrap-toc.js"></script>
<!-- Font Awesome icons -->
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous" />
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous" />
<!-- clipboard.js -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script>
<!-- headroom.js -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script>
<!-- pkgdown -->
<link href="../pkgdown.css" rel="stylesheet">
<script src="../pkgdown.js"></script>
<meta property="og:title" content="Bayesian Generalized Linear Models — Lrnr_bayesglm" />
<meta property="og:description" content="This learner provides fitting procedures for bayesian generalized linear
models (GLMs) from ar using bayesglm.fit. The GLMs
fitted in this way can incorporate independent normal, t, or Cauchy prior
distribution for the coefficients." />
<!-- 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]-->
<!-- Global site tag (gtag.js) - Google Analytics -->
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-115145808-1"></script>
<script>
window.dataLayer = window.dataLayer || [];
function gtag(){dataLayer.push(arguments);}
gtag('js', new Date());
gtag('config', 'UA-115145808-1');
</script>
</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">sl3</a>
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.4.3</span>
</span>
</div>
<div id="navbar" class="navbar-collapse collapse">
<ul class="nav navbar-nav">
<li>
<a href="https://tlverse.org">tlverse</a>
</li>
<li>
<a href="../index.html">sl3</a>
</li>
<li>
<a href="../reference/index.html">Reference</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/intro_sl3.html">Intro to sl3</a>
</li>
<li>
<a href="../articles/SuperLearner_benchmarks.html">sl3 Benchmarks</a>
</li>
<li>
<a href="../slides/sl3-slides.html">sl3 Presentation</a>
</li>
<li>
<a href="../articles/custom_lrnrs.html">Defining Custom sl3 Learners</a>
</li>
</ul>
</li>
</ul>
<ul class="nav navbar-nav navbar-right">
<li>
<a href="https://github.com/tlverse/sl3/">
<span class="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>Bayesian Generalized Linear Models</h1>
<small class="dont-index">Source: <a href='https://github.com/tlverse/sl3/blob/master/R/Lrnr_bayesglm.R'><code>R/Lrnr_bayesglm.R</code></a></small>
<div class="hidden name"><code>Lrnr_bayesglm.Rd</code></div>
</div>
<div class="ref-description">
<p>This learner provides fitting procedures for bayesian generalized linear
models (GLMs) from <span class="pkg">ar</span> using <code><a href='https://rdrr.io/pkg/arm/man/bayesglm.html'>bayesglm.fit</a></code>. The GLMs
fitted in this way can incorporate independent normal, t, or Cauchy prior
distribution for the coefficients.</p>
</div>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>An <code><a href='https://r6.r-lib.org/reference/R6Class.html'>R6Class</a></code> object inheriting from
<code><a href='Lrnr_base.html'>Lrnr_base</a></code>.</p>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A learner object inheriting from <code><a href='Lrnr_base.html'>Lrnr_base</a></code> with
methods for training and prediction. For a full list of learner
functionality, see the complete documentation of <code><a href='Lrnr_base.html'>Lrnr_base</a></code>.</p>
<h2 class="hasAnchor" id="parameters"><a class="anchor" href="#parameters"></a>Parameters</h2>
<ul>
<li><p><code>intercept = TRUE</code>: A <code>logical</code> specifying whether an intercept
term should be included in the fitted null model.</p></li>
<li><p><code>...</code>: Other parameters passed to <code><a href='https://rdrr.io/pkg/arm/man/bayesglm.html'>bayesglm.fit</a></code>.
See it's documentation for details.</p></li>
</ul>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p>Other Learners:
<code><a href='Custom_chain.html'>Custom_chain</a></code>,
<code><a href='Lrnr_HarmonicReg.html'>Lrnr_HarmonicReg</a></code>,
<code><a href='Lrnr_arima.html'>Lrnr_arima</a></code>,
<code><a href='Lrnr_bartMachine.html'>Lrnr_bartMachine</a></code>,
<code><a href='Lrnr_base.html'>Lrnr_base</a></code>,
<code><a href='Lrnr_bilstm.html'>Lrnr_bilstm</a></code>,
<code><a href='Lrnr_caret.html'>Lrnr_caret</a></code>,
<code><a href='Lrnr_cv_selector.html'>Lrnr_cv_selector</a></code>,
<code><a href='Lrnr_cv.html'>Lrnr_cv</a></code>,
<code><a href='Lrnr_dbarts.html'>Lrnr_dbarts</a></code>,
<code><a href='Lrnr_define_interactions.html'>Lrnr_define_interactions</a></code>,
<code><a href='Lrnr_density_discretize.html'>Lrnr_density_discretize</a></code>,
<code><a href='Lrnr_density_hse.html'>Lrnr_density_hse</a></code>,
<code><a href='Lrnr_density_semiparametric.html'>Lrnr_density_semiparametric</a></code>,
<code><a href='Lrnr_earth.html'>Lrnr_earth</a></code>,
<code><a href='Lrnr_expSmooth.html'>Lrnr_expSmooth</a></code>,
<code><a href='Lrnr_gam.html'>Lrnr_gam</a></code>,
<code><a href='Lrnr_gbm.html'>Lrnr_gbm</a></code>,
<code><a href='Lrnr_glm_fast.html'>Lrnr_glm_fast</a></code>,
<code><a href='Lrnr_glmnet.html'>Lrnr_glmnet</a></code>,
<code><a href='Lrnr_glm.html'>Lrnr_glm</a></code>,
<code><a href='Lrnr_grf.html'>Lrnr_grf</a></code>,
<code><a href='Lrnr_gru_keras.html'>Lrnr_gru_keras</a></code>,
<code><a href='Lrnr_gts.html'>Lrnr_gts</a></code>,
<code><a href='Lrnr_h2o_grid.html'>Lrnr_h2o_grid</a></code>,
<code><a href='Lrnr_hal9001.html'>Lrnr_hal9001</a></code>,
<code><a href='Lrnr_haldensify.html'>Lrnr_haldensify</a></code>,
<code><a href='Lrnr_hts.html'>Lrnr_hts</a></code>,
<code><a href='Lrnr_independent_binomial.html'>Lrnr_independent_binomial</a></code>,
<code><a href='Lrnr_lightgbm.html'>Lrnr_lightgbm</a></code>,
<code><a href='Lrnr_lstm_keras.html'>Lrnr_lstm_keras</a></code>,
<code><a href='Lrnr_mean.html'>Lrnr_mean</a></code>,
<code><a href='Lrnr_multiple_ts.html'>Lrnr_multiple_ts</a></code>,
<code><a href='Lrnr_multivariate.html'>Lrnr_multivariate</a></code>,
<code><a href='Lrnr_nnet.html'>Lrnr_nnet</a></code>,
<code><a href='Lrnr_nnls.html'>Lrnr_nnls</a></code>,
<code><a href='Lrnr_optim.html'>Lrnr_optim</a></code>,
<code><a href='Lrnr_pca.html'>Lrnr_pca</a></code>,
<code><a href='Lrnr_pkg_SuperLearner.html'>Lrnr_pkg_SuperLearner</a></code>,
<code><a href='Lrnr_polspline.html'>Lrnr_polspline</a></code>,
<code><a href='Lrnr_pooled_hazards.html'>Lrnr_pooled_hazards</a></code>,
<code><a href='Lrnr_randomForest.html'>Lrnr_randomForest</a></code>,
<code><a href='Lrnr_ranger.html'>Lrnr_ranger</a></code>,
<code><a href='Lrnr_revere_task.html'>Lrnr_revere_task</a></code>,
<code><a href='Lrnr_rpart.html'>Lrnr_rpart</a></code>,
<code><a href='Lrnr_rugarch.html'>Lrnr_rugarch</a></code>,
<code><a href='Lrnr_screener_augment.html'>Lrnr_screener_augment</a></code>,
<code><a href='Lrnr_screener_coefs.html'>Lrnr_screener_coefs</a></code>,
<code><a href='Lrnr_screener_correlation.html'>Lrnr_screener_correlation</a></code>,
<code><a href='Lrnr_screener_importance.html'>Lrnr_screener_importance</a></code>,
<code><a href='Lrnr_sl.html'>Lrnr_sl</a></code>,
<code><a href='Lrnr_solnp_density.html'>Lrnr_solnp_density</a></code>,
<code><a href='Lrnr_solnp.html'>Lrnr_solnp</a></code>,
<code><a href='Lrnr_stratified.html'>Lrnr_stratified</a></code>,
<code><a href='Lrnr_subset_covariates.html'>Lrnr_subset_covariates</a></code>,
<code><a href='Lrnr_svm.html'>Lrnr_svm</a></code>,
<code><a href='Lrnr_tsDyn.html'>Lrnr_tsDyn</a></code>,
<code><a href='Lrnr_ts_weights.html'>Lrnr_ts_weights</a></code>,
<code><a href='Lrnr_xgboost.html'>Lrnr_xgboost</a></code>,
<code><a href='Pipeline.html'>Pipeline</a></code>,
<code><a href='Stack.html'>Stack</a></code>,
<code><a href='define_h2o_X.html'>define_h2o_X</a>()</code>,
<code><a href='undocumented_learner.html'>undocumented_learner</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='fu'><a href='https://rdrr.io/r/utils/data.html'>data</a></span><span class='op'>(</span><span class='va'>cpp_imputed</span><span class='op'>)</span>
<span class='va'>covars</span> <span class='op'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>
<span class='st'>"apgar1"</span>, <span class='st'>"apgar5"</span>, <span class='st'>"parity"</span>, <span class='st'>"gagebrth"</span>, <span class='st'>"mage"</span>, <span class='st'>"meducyrs"</span>, <span class='st'>"sexn"</span>
<span class='op'>)</span>
<span class='va'>outcome</span> <span class='op'><-</span> <span class='st'>"haz"</span>
<span class='va'>task</span> <span class='op'><-</span> <span class='va'><a href='sl3_Task.html'>sl3_Task</a></span><span class='op'>$</span><span class='fu'>new</span><span class='op'>(</span><span class='va'>cpp_imputed</span>,
covariates <span class='op'>=</span> <span class='va'>covars</span>,
outcome <span class='op'>=</span> <span class='va'>outcome</span>
<span class='op'>)</span>
<span class='co'># fit and predict from a bayesian GLM</span>
<span class='va'>bayesglm_lrnr</span> <span class='op'><-</span> <span class='fu'><a href='Lrnr_base.html'>make_learner</a></span><span class='op'>(</span><span class='va'>Lrnr_bayesglm</span><span class='op'>)</span>
<span class='va'>bayesglm_fit</span> <span class='op'><-</span> <span class='va'>bayesglm_lrnr</span><span class='op'>$</span><span class='fu'>train</span><span class='op'>(</span><span class='va'>task</span><span class='op'>)</span>
<span class='va'>bayesglm_preds</span> <span class='op'><-</span> <span class='va'>bayesglm_fit</span><span class='op'>$</span><span class='fu'>predict</span><span class='op'>(</span><span class='va'>task</span><span class='op'>)</span>
</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 Jeremy Coyle, Nima Hejazi, Oleg Sofrygin, Ivana Malenica, Rachael Phillips.</p>
</div>
<div class="pkgdown">
<p>Site built with <a href="https://pkgdown.r-lib.org/">pkgdown</a> 1.6.1.</p>
</div>
</footer>
</div>
</body>
</html>