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
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
|
require(OpenMx)
options(mxCondenseMatrixSlots=TRUE)
# mxOption(NULL,"Default optimizer","NPSOL")
# mxOption(NULL,"Number of threads",2)
# mxOption(NULL,"Print level",20)
# mxOption(NULL,"Print file",3)
# mxOption(NULL,"Verify level",3)
require(mvtnorm)
#Generate data:
set.seed(476)
A1 <- matrix(0,100,100)
A1[lower.tri(A1)] <- runif(4950, -0.025, 0.025)
A1 <- A1 + t(A1)
diag(A1) <- runif(100,0.95,1.05)
A2 <- matrix(0,100,100)
A2[lower.tri(A2)] <- runif(4950, -0.025, 0.025)
A2 <- A2 + t(A2)
diag(A2) <- runif(100,0.95,1.05)
y <- t(rmvnorm(1,sigma=A1*0.25)+rmvnorm(1,sigma=A2*0.25))
y <- y + rnorm(100,sd=sqrt(0.5))
y[100] <- NA
x <- rnorm(100)
dat <- cbind(y,x)
colnames(dat) <- c("y","x")
plan <- mxComputeSequence(
steps=list(
mxComputeGradientDescent(engine=mxOption(NULL,"Default optimizer")),
mxComputeOnce('fitfunction', c('gradient','hessian')),
mxComputeStandardError(),
mxComputeHessianQuality(),
mxComputeReportDeriv(),
mxComputeReportExpectation()
))
test0 <- mxModel(
"GREMLtest",
plan,
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va1="A1",va2="A2",ve="I"),infoMatType="expected")
)
test0 <- mxRun(test0)
summary(test0)
omxCheckCloseEnough(test0$output$fit, 280.3646874, 1e-4)
omxCheckCloseEnough(coef(test0), c(0.5668669,-0.8059083,1.1844126), 1e-4)
omxCheckCloseEnough(test0$output$standardErrors[,1], c(1.2020943,0.8700919,0.8835703), 1e-4)
omxCheckCloseEnough(test0$output$gradient, c(-2.539113e-07, -3.300840e-07, -3.607828e-07), 1e-4)
omxCheckCloseEnough(test0$expectation$b[,1], c(-0.003919201,0.043639875), 1e-4)
omxCheckCloseEnough(vech(test0$expectation$bcov), c(0.0092116302,0.0003739306,0.0087043503), 1e-4)
test1sa <- mxModel(
"GREMLtest",
plan,
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va1="A1",va2="A2"),infoMatType="expected")
)
test1sa <- mxRun(test1sa)
summary(test1sa)
omxCheckCloseEnough(test0$output$fit, test1sa$output$fit, 1e-12)
omxCheckCloseEnough(coef(test0),coef(test1sa),1e-7)
omxCheckCloseEnough(test0$output$standardErrors,test1sa$output$standardErrors,1e-7)
omxCheckCloseEnough(test0$output$gradient,test1sa$output$gradient,2e-6)
omxCheckCloseEnough(test0$expectation$b,test1sa$expectation$b,1e-8)
omxCheckCloseEnough(test0$expectation$bcov,test1sa$expectation$bcov,1e-10)
test1num <- mxModel(
"GREMLtest",
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va1="A1",va2="A2"),autoDerivType="numeric",infoMatType="expected")
)
test1num <- mxRun(test1num)
summary(test1num)
omxCheckCloseEnough(test0$output$fit, test1num$output$fit, 5e-9)
omxCheckCloseEnough(coef(test0),coef(test1num),1e-5)
omxCheckCloseEnough(test0$output$standardErrors,test1num$output$standardErrors,0.05)
omxCheckCloseEnough(test0$output$gradient,test1num$output$gradient,5e-4)
omxCheckCloseEnough(test0$expectation$b,test1num$expectation$b,5e-6)
omxCheckCloseEnough(test0$expectation$bcov,test1num$expectation$bcov,1e-7)
test2sa <- mxModel(
"GREMLtest",
plan,
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va2="A2",ve="I"),infoMatType="expected")
)
test2sa <- mxRun(test2sa)
summary(test2sa)
omxCheckCloseEnough(test0$output$fit, test2sa$output$fit, 1e-12)
omxCheckCloseEnough(coef(test0),coef(test2sa),1e-7)
omxCheckCloseEnough(test0$output$standardErrors,test2sa$output$standardErrors,1e-8)
omxCheckCloseEnough(test0$output$gradient,test2sa$output$gradient,1e-6)
omxCheckCloseEnough(test0$expectation$b,test2sa$expectation$b,1e-9)
omxCheckCloseEnough(test0$expectation$bcov,test2sa$expectation$bcov,1e-10)
test2num <- mxModel(
"GREMLtest",
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va2="A2",ve="I"),autoDerivType="numeric",infoMatType="expected")
)
test2num <- mxRun(test2num)
summary(test2num)
omxCheckCloseEnough(test0$output$fit, test2num$output$fit, 5e-9)
omxCheckCloseEnough(coef(test0),coef(test2num),1e-5)
omxCheckCloseEnough(test0$output$standardErrors,test2num$output$standardErrors,0.05)
omxCheckCloseEnough(test0$output$gradient,test2num$output$gradient,5e-4)
omxCheckCloseEnough(test0$expectation$b,test2num$expectation$b,5e-6)
omxCheckCloseEnough(test0$expectation$bcov,test2num$expectation$bcov,1e-7)
test3sa <- mxModel(
"GREMLtest",
plan,
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va1="A1",ve="I"),infoMatType="expected")
)
test3sa <- mxRun(test3sa)
summary(test3sa)
omxCheckCloseEnough(test0$output$fit, test3sa$output$fit, 1e-12)
omxCheckCloseEnough(coef(test0),coef(test3sa),1e-7)
omxCheckCloseEnough(test0$output$standardErrors,test3sa$output$standardErrors,1e-7)
omxCheckCloseEnough(test0$output$gradient,test3sa$output$gradient,2e-6)
omxCheckCloseEnough(test0$expectation$b,test3sa$expectation$b,1e-8)
omxCheckCloseEnough(test0$expectation$bcov,test3sa$expectation$bcov,1e-10)
test3num <- mxModel(
"GREMLtest",
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va1="A1",ve="I"),autoDerivType="numeric",infoMatType="expected")
)
test3num <- mxRun(test3num)
summary(test3num)
omxCheckCloseEnough(test0$output$fit, test3num$output$fit, 5e-9)
omxCheckCloseEnough(coef(test0),coef(test3num),1e-5)
omxCheckCloseEnough(test0$output$standardErrors,test3num$output$standardErrors,0.05)
omxCheckCloseEnough(test0$output$gradient,test3num$output$gradient,5e-4)
omxCheckCloseEnough(test0$expectation$b,test3num$expectation$b,5e-6)
omxCheckCloseEnough(test0$expectation$bcov,test3num$expectation$bcov,1e-7)
test4sa <- mxModel(
"GREMLtest",
plan,
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(ve="I"),infoMatType="expected")
)
test4sa <- mxRun(test4sa)
summary(test4sa)
omxCheckCloseEnough(test0$output$fit, test4sa$output$fit, 1e-12)
omxCheckCloseEnough(coef(test0),coef(test4sa),1e-7)
omxCheckCloseEnough(test0$output$standardErrors,test4sa$output$standardErrors,1e-8)
omxCheckCloseEnough(test0$output$gradient,test4sa$output$gradient,1e-6)
omxCheckCloseEnough(test0$expectation$b,test4sa$expectation$b,1e-9)
omxCheckCloseEnough(test0$expectation$bcov,test4sa$expectation$bcov,1e-10)
test4num <- mxModel(
"GREMLtest",
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(ve="I"),autoDerivType="numeric",infoMatType="expected")
)
test4num <- mxRun(test4num)
summary(test4num)
omxCheckCloseEnough(test0$output$fit, test4num$output$fit, 5e-9)
omxCheckCloseEnough(coef(test0),coef(test4num),1e-5)
omxCheckCloseEnough(test0$output$standardErrors,test4num$output$standardErrors,0.05)
omxCheckCloseEnough(test0$output$gradient,test4num$output$gradient,5e-4)
omxCheckCloseEnough(test0$expectation$b,test4num$expectation$b,5e-6)
omxCheckCloseEnough(test0$expectation$bcov,test4num$expectation$bcov,1e-7)
test5sa <- mxModel(
"GREMLtest",
plan,
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va1="A1"),infoMatType="expected")
)
test5sa <- mxRun(test5sa)
summary(test5sa)
omxCheckCloseEnough(test0$output$fit, test5sa$output$fit, 1e-12)
omxCheckCloseEnough(coef(test0),coef(test5sa),1e-7)
omxCheckCloseEnough(test0$output$standardErrors,test5sa$output$standardErrors,1e-8)
omxCheckCloseEnough(test0$output$gradient,test5sa$output$gradient,1e-6)
omxCheckCloseEnough(test0$expectation$b,test5sa$expectation$b,1e-9)
omxCheckCloseEnough(test0$expectation$bcov,test5sa$expectation$bcov,1e-10)
test5num <- mxModel(
"GREMLtest",
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va1="A1"),autoDerivType="numeric",infoMatType="expected")
)
test5num <- mxRun(test5num)
summary(test5num)
omxCheckCloseEnough(test0$output$fit, test5num$output$fit, 5e-9)
omxCheckCloseEnough(coef(test0),coef(test5num),1e-5)
omxCheckCloseEnough(test0$output$standardErrors,test5num$output$standardErrors,0.05)
omxCheckCloseEnough(test0$output$gradient,test5num$output$gradient,5e-4)
omxCheckCloseEnough(test0$expectation$b,test5num$expectation$b,5e-6)
omxCheckCloseEnough(test0$expectation$bcov,test5num$expectation$bcov,1e-7)
test6sa <- mxModel(
"GREMLtest",
plan,
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va2="A2"),infoMatType="expected")
)
test6sa <- mxRun(test6sa)
summary(test6sa)
omxCheckCloseEnough(test0$output$fit, test6sa$output$fit, 1e-12)
omxCheckCloseEnough(coef(test0),coef(test6sa),1e-7)
omxCheckCloseEnough(test0$output$standardErrors,test6sa$output$standardErrors,1e-8)
omxCheckCloseEnough(test0$output$gradient,test6sa$output$gradient,1e-6)
omxCheckCloseEnough(test0$expectation$b,test6sa$expectation$b,1e-9)
omxCheckCloseEnough(test0$expectation$bcov,test6sa$expectation$bcov,1e-10)
test6num <- mxModel(
"GREMLtest",
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values =0.5, labels = "ve", lbound = 0.0001,
name = "Ve"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.25, labels = "va1", name = "Va1"),
mxMatrix(type = "Full", nrow = 1, ncol=1, free=T, values = 0.20, labels = "va2", name = "Va2"),
mxData(observed = dat, type="raw", sort=FALSE),
mxExpectationGREML(V="V",yvars="y", Xvars="x", addOnes=T),
mxMatrix("Iden",nrow=100,name="I"),
mxMatrix("Symm",nrow=100,free=F,values=A1,name="A1"),
mxMatrix("Symm",nrow=100,free=F,values=A2,name="A2"),
mxAlgebra((A1%x%Va1) + (A2%x%Va2) + (I%x%Ve), name="V"),
mxFitFunctionGREML(dV=c(va2="A2"),autoDerivType="numeric",infoMatType="expected")
)
test6num <- mxRun(test6num)
summary(test6num)
omxCheckCloseEnough(test0$output$fit, test6num$output$fit, 5e-9)
omxCheckCloseEnough(coef(test0),coef(test6num),1e-5)
omxCheckCloseEnough(test0$output$standardErrors,test6num$output$standardErrors,0.05)
omxCheckCloseEnough(test0$output$gradient,test6num$output$gradient,5e-4)
omxCheckCloseEnough(test0$expectation$b,test6num$expectation$b,5e-6)
omxCheckCloseEnough(test0$expectation$bcov,test6num$expectation$bcov,1e-7)
|
