gonad_mature: Estimate gonadal maturity

Description Usage Arguments Details Value Examples

View source: R/gonadMat-main.R

Description

Estimate size at gonad maturity.

Usage

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gonad_mature(data, varNames = c("allometric", "stage"),
  inmName = "inm", matName = "mad", method = "fq", niter = 999,
  seed = 70388)

Arguments

data

data.frame with allometric variables and stage of sexual maturity (gonad maturation stages).

varNames

a character string indicating the name of the allometric and the stage of sexual maturity variables to be used for analysis.

inmName

a character string indicating the name or names of the inmaturity stage.

matName

a character string indicating the name or names of the maturity stage.

method

a character string indicating the method to be applied, "fq" frecuentist GLM, or "bayes" Bayes GLM (MCMClogit function).

niter

number of iterations (bootstrap resampling).

seed

a single value, interpreted as an integer.

Details

Estimate the size at gonad maturity using a logistic regression with X variable and stages of sexual maturity (two categories: inmature and mature).

The function requires a data.frame with the X (allometric variable) and the stage of sexual maturity (gonad maturation stage).

The argument varNames requires a character string indicating the name of one allometric and the stage of sexual maturity variable to be used for analysis (i.e varNames = c("total_length", "stage_mat")). So the argument varNames must contain two character strings only, the first is the allometric variable and the second is the stage of sexual maturity.

The arguments inmName and matName require a character string indicanting the name of the stages of sexual maturity in the data.frame. The argument could contain one character string or could be a vector (i.e inmName = "I", matName = c("II", "III", "IV")).

The argument method requires a character string indicating which regression will be used for the test. If method = "fq" the logistic regression is based on GLM (frequentist), if method = "bayes" a sample from the posterior distribution of a logistic regression model using a random walk Metropolis algorithm is generated (see MCMClogit function).

The argument niter requires a number. For the GLM regression (method = "fq"), a non-parametric bootstrap method consists in generate B bootstrap samples, by resampling with replacement the original data. Then all statistics for each parameter can be calculated from each bootstrap sample (median and confidence intervals). For the method = "bayes", the argument niter is related to the number of Metropolis iterations for the sampler.

Value

An object of class 'gonadMat'.

model the summary statistics of the model.

A_boot the 'n iter' values of parameter A.

B_boot the 'n iter' values of parameter B.

L50 the 'n iter' values of parameter L50 (size at gonad maturity).

out a dataframe with the allometric variable "X", stage of sexual maturity, the fitted values for logistic regression and confidence intervals (95%). Also the summary statistics of the model is provided.

Examples

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data(matFish)

gonad_mat = gonad_mature(matFish, varNames = c("total_length", "stage_mat"), inmName = "I", 
matName = c("II", "III", "IV"), method = "fq", niter = 50)

# 'niter' parameters:
gonad_mat$A_boot
gonad_mat$B_boot
gonad_mat$L50_boot
gonad_mat$out

Example output

 [1] -8.627030 -8.792177 -9.348871 -9.087148 -9.006368 -8.264212 -8.258821
 [8] -8.566862 -8.931090 -8.421382 -8.594158 -9.422902 -8.159287 -7.924324
[15] -7.816051 -8.649295 -8.441946 -7.897699 -8.527981 -9.050438 -8.726487
[22] -8.885475 -8.698325 -9.182506 -8.658300 -8.759841 -8.032643 -8.024464
[29] -8.925118 -8.583064 -8.753981 -7.831774 -8.502496 -8.475411 -8.597212
[36] -8.345696 -8.702437 -8.949270 -8.950208 -8.671547 -8.777397 -8.749831
[43] -8.070171 -9.388672 -8.190737 -8.157404 -8.741321 -8.232945 -8.610317
[50] -8.588924
 [1] 0.3568461 0.3668552 0.3869750 0.3733971 0.3689496 0.3452642 0.3410802
 [8] 0.3530922 0.3744906 0.3456040 0.3550986 0.3888834 0.3370025 0.3274486
[15] 0.3226383 0.3554968 0.3417472 0.3262718 0.3523094 0.3713010 0.3577442
[22] 0.3670733 0.3632974 0.3772265 0.3540632 0.3617494 0.3359198 0.3351658
[29] 0.3677076 0.3528702 0.3598843 0.3230251 0.3496224 0.3414643 0.3511483
[36] 0.3435701 0.3643522 0.3761087 0.3714209 0.3571104 0.3602560 0.3659014
[43] 0.3371633 0.3927777 0.3428081 0.3423900 0.3631556 0.3430552 0.3550637
[50] 0.3513234
 [1] 24.17577 23.96634 24.15885 24.33642 24.41084 23.93591 24.21372 24.26239
 [9] 23.84864 24.36715 24.20218 24.23066 24.21135 24.20021 24.22543 24.33016
[17] 24.70231 24.20589 24.20594 24.37494 24.39309 24.20627 23.94271 24.34215
[25] 24.45411 24.21522 23.91238 23.94177 24.27232 24.32357 24.32443 24.24509
[33] 24.31908 24.82078 24.48314 24.29110 23.88468 23.79437 24.09721 24.28254
[41] 24.36433 23.91309 23.93549 23.90327 23.89307 23.82489 24.07046 23.99890
[49] 24.25006 24.44734
      x mature CIlower fitted CIupper
1    12      0   0.009  0.013   0.019
2    12      0   0.009  0.013   0.019
3    13      0   0.013  0.018   0.026
4    14      0   0.019  0.025   0.035
5    14      0   0.019  0.025   0.035
6    14      0   0.019  0.025   0.035
7    14      0   0.019  0.025   0.035
8    14      0   0.019  0.025   0.035
9    14      0   0.019  0.025   0.035
10   15      0   0.028  0.036   0.048
11   15      0   0.028  0.036   0.048
12   15      0   0.028  0.036   0.048
13   15      0   0.028  0.036   0.048
14   15      0   0.028  0.036   0.048
15   15      0   0.028  0.036   0.048
16   15      0   0.028  0.036   0.048
17   15      0   0.028  0.036   0.048
18   15      0   0.028  0.036   0.048
19   15      0   0.028  0.036   0.048
20   16      0   0.041  0.051   0.065
21   16      0   0.041  0.051   0.065
22   16      0   0.041  0.051   0.065
23   16      0   0.041  0.051   0.065
24   16      0   0.041  0.051   0.065
25   16      0   0.041  0.051   0.065
26   16      0   0.041  0.051   0.065
27   16      0   0.041  0.051   0.065
28   16      0   0.041  0.051   0.065
29   16      0   0.041  0.051   0.065
30   16      0   0.041  0.051   0.065
31   16      0   0.041  0.051   0.065
32   16      0   0.041  0.051   0.065
33   16      0   0.041  0.051   0.065
34   16      0   0.041  0.051   0.065
35   16      0   0.041  0.051   0.065
36   16      0   0.041  0.051   0.065
37   16      0   0.041  0.051   0.065
38   16      0   0.041  0.051   0.065
39   17      0   0.059  0.071   0.089
40   17      0   0.059  0.071   0.089
41   17      0   0.059  0.071   0.089
42   17      0   0.059  0.071   0.089
43   17      0   0.059  0.071   0.089
44   17      0   0.059  0.071   0.089
45   17      0   0.059  0.071   0.089
46   17      0   0.059  0.071   0.089
47   17      0   0.059  0.071   0.089
48   17      0   0.059  0.071   0.089
49   17      0   0.059  0.071   0.089
50   17      0   0.059  0.071   0.089
51   17      0   0.059  0.071   0.089
52   17      0   0.059  0.071   0.089
53   17      0   0.059  0.071   0.089
54   17      0   0.059  0.071   0.089
55   17      0   0.059  0.071   0.089
56   17      0   0.059  0.071   0.089
57   17      0   0.059  0.071   0.089
58   17      0   0.059  0.071   0.089
59   17      0   0.059  0.071   0.089
60   17      0   0.059  0.071   0.089
61   17      0   0.059  0.071   0.089
62   17      0   0.059  0.071   0.089
63   17      0   0.059  0.071   0.089
64   17      0   0.059  0.071   0.089
65   17      0   0.059  0.071   0.089
66   17      0   0.059  0.071   0.089
67   17      0   0.059  0.071   0.089
68   18      0   0.084  0.099   0.120
69   18      0   0.084  0.099   0.120
70   18      0   0.084  0.099   0.120
71   18      0   0.084  0.099   0.120
72   18      0   0.084  0.099   0.120
73   18      0   0.084  0.099   0.120
74   18      0   0.084  0.099   0.120
75   18      0   0.084  0.099   0.120
76   18      0   0.084  0.099   0.120
77   18      0   0.084  0.099   0.120
78   18      0   0.084  0.099   0.120
79   18      0   0.084  0.099   0.120
80   18      0   0.084  0.099   0.120
81   18      0   0.084  0.099   0.120
82   18      0   0.084  0.099   0.120
83   18      0   0.084  0.099   0.120
84   18      0   0.084  0.099   0.120
85   18      0   0.084  0.099   0.120
86   18      0   0.084  0.099   0.120
87   18      0   0.084  0.099   0.120
88   18      0   0.084  0.099   0.120
89   18      0   0.084  0.099   0.120
90   18      0   0.084  0.099   0.120
91   18      0   0.084  0.099   0.120
92   18      0   0.084  0.099   0.120
93   19      0   0.118  0.135   0.161
94   19      0   0.118  0.135   0.161
95   19      0   0.118  0.135   0.161
96   19      0   0.118  0.135   0.161
97   19      0   0.118  0.135   0.161
98   19      0   0.118  0.135   0.161
99   19      0   0.118  0.135   0.161
100  19      0   0.118  0.135   0.161
101  19      0   0.118  0.135   0.161
102  19      0   0.118  0.135   0.161
103  19      0   0.118  0.135   0.161
104  19      0   0.118  0.135   0.161
105  19      0   0.118  0.135   0.161
106  19      0   0.118  0.135   0.161
107  19      0   0.118  0.135   0.161
108  19      0   0.118  0.135   0.161
109  19      0   0.118  0.135   0.161
110  19      0   0.118  0.135   0.161
111  19      0   0.118  0.135   0.161
112  19      0   0.118  0.135   0.161
113  19      0   0.118  0.135   0.161
114  19      0   0.118  0.135   0.161
115  19      0   0.118  0.135   0.161
116  19      0   0.118  0.135   0.161
117  19      0   0.118  0.135   0.161
118  19      0   0.118  0.135   0.161
119  19      0   0.118  0.135   0.161
120  19      0   0.118  0.135   0.161
121  19      0   0.118  0.135   0.161
122  19      0   0.118  0.135   0.161
123  19      0   0.118  0.135   0.161
124  19      0   0.118  0.135   0.161
125  19      0   0.118  0.135   0.161
126  20      0   0.162  0.181   0.212
127  20      0   0.162  0.181   0.212
128  20      0   0.162  0.181   0.212
129  20      0   0.162  0.181   0.212
130  20      0   0.162  0.181   0.212
131  20      0   0.162  0.181   0.212
132  20      0   0.162  0.181   0.212
133  20      0   0.162  0.181   0.212
134  20      0   0.162  0.181   0.212
135  20      0   0.162  0.181   0.212
136  20      0   0.162  0.181   0.212
137  20      0   0.162  0.181   0.212
138  20      0   0.162  0.181   0.212
139  20      0   0.162  0.181   0.212
140  20      0   0.162  0.181   0.212
141  20      0   0.162  0.181   0.212
142  20      0   0.162  0.181   0.212
143  20      0   0.162  0.181   0.212
144  20      0   0.162  0.181   0.212
145  20      0   0.162  0.181   0.212
146  20      0   0.162  0.181   0.212
147  20      0   0.162  0.181   0.212
148  20      0   0.162  0.181   0.212
149  20      0   0.162  0.181   0.212
150  20      0   0.162  0.181   0.212
151  20      0   0.162  0.181   0.212
152  20      0   0.162  0.181   0.212
153  20      0   0.162  0.181   0.212
154  20      0   0.162  0.181   0.212
155  20      0   0.162  0.181   0.212
156  20      0   0.162  0.181   0.212
157  20      0   0.162  0.181   0.212
158  20      0   0.162  0.181   0.212
159  21      0   0.220  0.241   0.273
160  21      0   0.220  0.241   0.273
161  21      0   0.220  0.241   0.273
162  21      0   0.220  0.241   0.273
163  21      0   0.220  0.241   0.273
164  21      0   0.220  0.241   0.273
165  21      0   0.220  0.241   0.273
166  21      0   0.220  0.241   0.273
167  21      0   0.220  0.241   0.273
168  21      0   0.220  0.241   0.273
169  21      0   0.220  0.241   0.273
170  21      0   0.220  0.241   0.273
171  21      0   0.220  0.241   0.273
172  21      0   0.220  0.241   0.273
173  21      0   0.220  0.241   0.273
174  21      0   0.220  0.241   0.273
175  21      0   0.220  0.241   0.273
176  21      0   0.220  0.241   0.273
177  21      0   0.220  0.241   0.273
178  21      0   0.220  0.241   0.273
179  21      0   0.220  0.241   0.273
180  21      0   0.220  0.241   0.273
181  21      0   0.220  0.241   0.273
182  21      0   0.220  0.241   0.273
183  21      0   0.220  0.241   0.273
184  21      0   0.220  0.241   0.273
185  21      0   0.220  0.241   0.273
186  21      0   0.220  0.241   0.273
187  21      0   0.220  0.241   0.273
188  21      0   0.220  0.241   0.273
189  21      0   0.220  0.241   0.273
190  21      0   0.220  0.241   0.273
191  21      0   0.220  0.241   0.273
192  21      0   0.220  0.241   0.273
193  21      0   0.220  0.241   0.273
194  21      0   0.220  0.241   0.273
195  21      0   0.220  0.241   0.273
196  21      0   0.220  0.241   0.273
197  21      0   0.220  0.241   0.273
198  21      0   0.220  0.241   0.273
199  21      0   0.220  0.241   0.273
200  21      0   0.220  0.241   0.273
201  21      0   0.220  0.241   0.273
202  21      0   0.220  0.241   0.273
203  21      0   0.220  0.241   0.273
204  21      0   0.220  0.241   0.273
205  21      0   0.220  0.241   0.273
206  21      0   0.220  0.241   0.273
207  21      0   0.220  0.241   0.273
208  22      0   0.286  0.313   0.344
209  22      0   0.286  0.313   0.344
210  22      0   0.286  0.313   0.344
211  22      0   0.286  0.313   0.344
212  22      0   0.286  0.313   0.344
213  22      0   0.286  0.313   0.344
214  22      0   0.286  0.313   0.344
215  22      0   0.286  0.313   0.344
216  22      0   0.286  0.313   0.344
217  22      0   0.286  0.313   0.344
218  22      0   0.286  0.313   0.344
219  22      0   0.286  0.313   0.344
220  22      0   0.286  0.313   0.344
221  22      0   0.286  0.313   0.344
222  22      0   0.286  0.313   0.344
223  22      0   0.286  0.313   0.344
224  22      0   0.286  0.313   0.344
225  22      0   0.286  0.313   0.344
226  22      0   0.286  0.313   0.344
227  22      0   0.286  0.313   0.344
228  22      0   0.286  0.313   0.344
229  22      0   0.286  0.313   0.344
230  22      0   0.286  0.313   0.344
231  22      0   0.286  0.313   0.344
232  22      0   0.286  0.313   0.344
233  22      0   0.286  0.313   0.344
234  22      0   0.286  0.313   0.344
235  22      0   0.286  0.313   0.344
236  22      0   0.286  0.313   0.344
237  22      0   0.286  0.313   0.344
238  22      0   0.286  0.313   0.344
239  22      0   0.286  0.313   0.344
240  22      0   0.286  0.313   0.344
241  22      0   0.286  0.313   0.344
242  22      0   0.286  0.313   0.344
243  22      0   0.286  0.313   0.344
244  22      0   0.286  0.313   0.344
245  22      0   0.286  0.313   0.344
246  22      0   0.286  0.313   0.344
247  22      0   0.286  0.313   0.344
248  22      0   0.286  0.313   0.344
249  22      0   0.286  0.313   0.344
250  22      0   0.286  0.313   0.344
251  22      0   0.286  0.313   0.344
252  22      0   0.286  0.313   0.344
253  22      0   0.286  0.313   0.344
254  22      0   0.286  0.313   0.344
255  22      0   0.286  0.313   0.344
256  22      0   0.286  0.313   0.344
257  22      0   0.286  0.313   0.344
258  22      0   0.286  0.313   0.344
259  22      0   0.286  0.313   0.344
260  22      0   0.286  0.313   0.344
261  22      0   0.286  0.313   0.344
262  22      0   0.286  0.313   0.344
263  22      0   0.286  0.313   0.344
264  22      0   0.286  0.313   0.344
265  22      0   0.286  0.313   0.344
266  22      0   0.286  0.313   0.344
267  22      0   0.286  0.313   0.344
268  22      0   0.286  0.313   0.344
269  22      0   0.286  0.313   0.344
270  23      0   0.362  0.393   0.425
271  23      0   0.362  0.393   0.425
272  23      0   0.362  0.393   0.425
273  23      0   0.362  0.393   0.425
274  23      0   0.362  0.393   0.425
275  23      0   0.362  0.393   0.425
276  23      0   0.362  0.393   0.425
277  23      0   0.362  0.393   0.425
278  23      0   0.362  0.393   0.425
279  23      0   0.362  0.393   0.425
280  23      0   0.362  0.393   0.425
281  23      0   0.362  0.393   0.425
282  23      0   0.362  0.393   0.425
283  23      0   0.362  0.393   0.425
284  23      0   0.362  0.393   0.425
285  23      0   0.362  0.393   0.425
286  23      0   0.362  0.393   0.425
287  23      0   0.362  0.393   0.425
288  23      0   0.362  0.393   0.425
289  23      0   0.362  0.393   0.425
290  23      0   0.362  0.393   0.425
291  23      0   0.362  0.393   0.425
292  23      0   0.362  0.393   0.425
293  23      0   0.362  0.393   0.425
294  23      0   0.362  0.393   0.425
295  23      0   0.362  0.393   0.425
296  23      0   0.362  0.393   0.425
297  23      0   0.362  0.393   0.425
298  23      0   0.362  0.393   0.425
299  23      0   0.362  0.393   0.425
300  23      0   0.362  0.393   0.425
301  23      0   0.362  0.393   0.425
302  23      0   0.362  0.393   0.425
303  23      0   0.362  0.393   0.425
304  23      0   0.362  0.393   0.425
305  23      0   0.362  0.393   0.425
306  23      0   0.362  0.393   0.425
307  23      0   0.362  0.393   0.425
308  23      0   0.362  0.393   0.425
309  23      0   0.362  0.393   0.425
310  23      0   0.362  0.393   0.425
311  23      0   0.362  0.393   0.425
312  23      0   0.362  0.393   0.425
313  23      0   0.362  0.393   0.425
314  23      0   0.362  0.393   0.425
315  23      0   0.362  0.393   0.425
316  23      0   0.362  0.393   0.425
317  23      0   0.362  0.393   0.425
318  23      0   0.362  0.393   0.425
319  23      0   0.362  0.393   0.425
320  23      0   0.362  0.393   0.425
321  23      0   0.362  0.393   0.425
322  23      0   0.362  0.393   0.425
323  23      0   0.362  0.393   0.425
324  23      0   0.362  0.393   0.425
325  23      0   0.362  0.393   0.425
326  23      0   0.362  0.393   0.425
327  23      0   0.362  0.393   0.425
328  23      0   0.362  0.393   0.425
329  23      0   0.362  0.393   0.425
330  23      0   0.362  0.393   0.425
331  23      0   0.362  0.393   0.425
332  23      0   0.362  0.393   0.425
333  24      0   0.444  0.481   0.515
334  24      0   0.444  0.481   0.515
335  24      0   0.444  0.481   0.515
336  24      0   0.444  0.481   0.515
337  24      0   0.444  0.481   0.515
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478  29      0   0.815  0.845   0.876
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494  30      0   0.861  0.885   0.911
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499  31      0   0.896  0.917   0.937
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512  35      0   0.970  0.979   0.985
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515  38      0   0.989  0.992   0.995
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519  18      1   0.084  0.099   0.120
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521  19      1   0.118  0.135   0.161
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552  22      1   0.286  0.313   0.344
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587  23      1   0.362  0.393   0.425
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713  26      1   0.614  0.651   0.694
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754  26      1   0.614  0.651   0.694
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756  26      1   0.614  0.651   0.694
757  26      1   0.614  0.651   0.694
758  26      1   0.614  0.651   0.694
759  26      1   0.614  0.651   0.694
760  26      1   0.614  0.651   0.694
761  26      1   0.614  0.651   0.694
762  26      1   0.614  0.651   0.694
763  26      1   0.614  0.651   0.694
764  26      1   0.614  0.651   0.694
765  26      1   0.614  0.651   0.694
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767  26      1   0.614  0.651   0.694
768  26      1   0.614  0.651   0.694
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770  26      1   0.614  0.651   0.694
771  26      1   0.614  0.651   0.694
772  26      1   0.614  0.651   0.694
773  27      1   0.691  0.729   0.769
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780  27      1   0.691  0.729   0.769
781  27      1   0.691  0.729   0.769
782  27      1   0.691  0.729   0.769
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785  27      1   0.691  0.729   0.769
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790  27      1   0.691  0.729   0.769
791  27      1   0.691  0.729   0.769
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793  27      1   0.691  0.729   0.769
794  27      1   0.691  0.729   0.769
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796  27      1   0.691  0.729   0.769
797  27      1   0.691  0.729   0.769
798  27      1   0.691  0.729   0.769
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801  27      1   0.691  0.729   0.769
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810  27      1   0.691  0.729   0.769
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812  27      1   0.691  0.729   0.769
813  27      1   0.691  0.729   0.769
814  27      1   0.691  0.729   0.769
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816  27      1   0.691  0.729   0.769
817  27      1   0.691  0.729   0.769
818  27      1   0.691  0.729   0.769
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820  27      1   0.691  0.729   0.769
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825  27      1   0.691  0.729   0.769
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829  27      1   0.691  0.729   0.769
830  27      1   0.691  0.729   0.769
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832  27      1   0.691  0.729   0.769
833  27      1   0.691  0.729   0.769
834  27      1   0.691  0.729   0.769
835  27      1   0.691  0.729   0.769
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837  27      1   0.691  0.729   0.769
838  28      1   0.759  0.794   0.829
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840  28      1   0.759  0.794   0.829
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891  28      1   0.759  0.794   0.829
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893  28      1   0.759  0.794   0.829
894  28      1   0.759  0.794   0.829
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896  28      1   0.759  0.794   0.829
897  28      1   0.759  0.794   0.829
898  28      1   0.759  0.794   0.829
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900  28      1   0.759  0.794   0.829
901  28      1   0.759  0.794   0.829
902  29      1   0.815  0.845   0.876
903  29      1   0.815  0.845   0.876
904  29      1   0.815  0.845   0.876
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906  29      1   0.815  0.845   0.876
907  29      1   0.815  0.845   0.876
908  29      1   0.815  0.845   0.876
909  29      1   0.815  0.845   0.876
910  29      1   0.815  0.845   0.876
911  29      1   0.815  0.845   0.876
912  29      1   0.815  0.845   0.876
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915  29      1   0.815  0.845   0.876
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920  29      1   0.815  0.845   0.876
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924  29      1   0.815  0.845   0.876
925  29      1   0.815  0.845   0.876
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930  29      1   0.815  0.845   0.876
931  29      1   0.815  0.845   0.876
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933  29      1   0.815  0.845   0.876
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937  29      1   0.815  0.845   0.876
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940  29      1   0.815  0.845   0.876
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950  29      1   0.815  0.845   0.876
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957  29      1   0.815  0.845   0.876
958  29      1   0.815  0.845   0.876
959  30      1   0.861  0.885   0.911
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963  30      1   0.861  0.885   0.911
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967  30      1   0.861  0.885   0.911
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969  30      1   0.861  0.885   0.911
970  30      1   0.861  0.885   0.911
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978  30      1   0.861  0.885   0.911
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980  30      1   0.861  0.885   0.911
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987  30      1   0.861  0.885   0.911
988  30      1   0.861  0.885   0.911
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1000 30      1   0.861  0.885   0.911
1001 30      1   0.861  0.885   0.911
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1005 30      1   0.861  0.885   0.911
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1007 30      1   0.861  0.885   0.911
1008 30      1   0.861  0.885   0.911
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1016 30      1   0.861  0.885   0.911
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1020 30      1   0.861  0.885   0.911
1021 30      1   0.861  0.885   0.911
1022 30      1   0.861  0.885   0.911
1023 30      1   0.861  0.885   0.911
1024 30      1   0.861  0.885   0.911
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1031 30      1   0.861  0.885   0.911
1032 31      1   0.896  0.917   0.937
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1034 31      1   0.896  0.917   0.937
1035 31      1   0.896  0.917   0.937
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1037 31      1   0.896  0.917   0.937
1038 31      1   0.896  0.917   0.937
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1080 31      1   0.896  0.917   0.937
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1100 31      1   0.896  0.917   0.937
1101 31      1   0.896  0.917   0.937
1102 31      1   0.896  0.917   0.937
1103 31      1   0.896  0.917   0.937
1104 32      1   0.924  0.940   0.956
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1111 32      1   0.924  0.940   0.956
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1120 32      1   0.924  0.940   0.956
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1161 32      1   0.924  0.940   0.956
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1572 40      1   0.994  0.996   0.998
1573 40      1   0.994  0.996   0.998
1574 40      1   0.994  0.996   0.998
1575 40      1   0.994  0.996   0.998
1576 40      1   0.994  0.996   0.998
1577 40      1   0.994  0.996   0.998
1578 40      1   0.994  0.996   0.998
1579 40      1   0.994  0.996   0.998
1580 40      1   0.994  0.996   0.998
1581 40      1   0.994  0.996   0.998
1582 40      1   0.994  0.996   0.998
1583 40      1   0.994  0.996   0.998
1584 40      1   0.994  0.996   0.998
1585 41      1   0.996  0.997   0.999
1586 41      1   0.996  0.997   0.999
1587 41      1   0.996  0.997   0.999
1588 41      1   0.996  0.997   0.999
1589 41      1   0.996  0.997   0.999
1590 41      1   0.996  0.997   0.999
1591 41      1   0.996  0.997   0.999
1592 41      1   0.996  0.997   0.999
1593 41      1   0.996  0.997   0.999
1594 41      1   0.996  0.997   0.999
1595 41      1   0.996  0.997   0.999
1596 41      1   0.996  0.997   0.999
1597 41      1   0.996  0.997   0.999
1598 41      1   0.996  0.997   0.999
1599 41      1   0.996  0.997   0.999
1600 41      1   0.996  0.997   0.999
1601 41      1   0.996  0.997   0.999
1602 41      1   0.996  0.997   0.999
1603 41      1   0.996  0.997   0.999
1604 42      1   0.997  0.998   0.999
1605 42      1   0.997  0.998   0.999
1606 42      1   0.997  0.998   0.999
1607 42      1   0.997  0.998   0.999
1608 42      1   0.997  0.998   0.999
1609 42      1   0.997  0.998   0.999
1610 42      1   0.997  0.998   0.999
1611 42      1   0.997  0.998   0.999
1612 42      1   0.997  0.998   0.999
1613 42      1   0.997  0.998   0.999
1614 42      1   0.997  0.998   0.999
1615 42      1   0.997  0.998   0.999
1616 42      1   0.997  0.998   0.999
1617 42      1   0.997  0.998   0.999
1618 42      1   0.997  0.998   0.999
1619 42      1   0.997  0.998   0.999
1620 42      1   0.997  0.998   0.999
1621 42      1   0.997  0.998   0.999
1622 42      1   0.997  0.998   0.999
1623 42      1   0.997  0.998   0.999
1624 42      1   0.997  0.998   0.999
1625 42      1   0.997  0.998   0.999
1626 43      1   0.998  0.999   0.999
1627 43      1   0.998  0.999   0.999
1628 43      1   0.998  0.999   0.999
1629 43      1   0.998  0.999   0.999
1630 43      1   0.998  0.999   0.999
1631 43      1   0.998  0.999   0.999
1632 43      1   0.998  0.999   0.999
1633 43      1   0.998  0.999   0.999
1634 43      1   0.998  0.999   0.999
1635 43      1   0.998  0.999   0.999
1636 43      1   0.998  0.999   0.999
1637 43      1   0.998  0.999   0.999
1638 43      1   0.998  0.999   0.999
1639 43      1   0.998  0.999   0.999
1640 43      1   0.998  0.999   0.999
1641 43      1   0.998  0.999   0.999
1642 43      1   0.998  0.999   0.999
1643 44      1   0.998  0.999   1.000
1644 44      1   0.998  0.999   1.000
1645 44      1   0.998  0.999   1.000
1646 44      1   0.998  0.999   1.000
1647 44      1   0.998  0.999   1.000
1648 44      1   0.998  0.999   1.000
1649 44      1   0.998  0.999   1.000
1650 44      1   0.998  0.999   1.000
1651 44      1   0.998  0.999   1.000
1652 44      1   0.998  0.999   1.000
1653 44      1   0.998  0.999   1.000
1654 44      1   0.998  0.999   1.000
1655 44      1   0.998  0.999   1.000
1656 44      1   0.998  0.999   1.000
1657 44      1   0.998  0.999   1.000
1658 44      1   0.998  0.999   1.000
1659 45      1   0.999  0.999   1.000
1660 45      1   0.999  0.999   1.000
1661 45      1   0.999  0.999   1.000
1662 45      1   0.999  0.999   1.000
1663 45      1   0.999  0.999   1.000
1664 45      1   0.999  0.999   1.000
1665 45      1   0.999  0.999   1.000
1666 45      1   0.999  0.999   1.000
1667 45      1   0.999  0.999   1.000
1668 45      1   0.999  0.999   1.000
1669 45      1   0.999  0.999   1.000
1670 45      1   0.999  0.999   1.000
1671 45      1   0.999  0.999   1.000
1672 46      1   0.999  1.000   1.000
1673 46      1   0.999  1.000   1.000
1674 46      1   0.999  1.000   1.000
1675 46      1   0.999  1.000   1.000
1676 46      1   0.999  1.000   1.000
1677 46      1   0.999  1.000   1.000
1678 46      1   0.999  1.000   1.000
1679 46      1   0.999  1.000   1.000
1680 46      1   0.999  1.000   1.000
1681 46      1   0.999  1.000   1.000
1682 46      1   0.999  1.000   1.000
1683 46      1   0.999  1.000   1.000
1684 46      1   0.999  1.000   1.000
1685 46      1   0.999  1.000   1.000
1686 47      1   0.999  1.000   1.000
1687 47      1   0.999  1.000   1.000
1688 47      1   0.999  1.000   1.000
1689 47      1   0.999  1.000   1.000
1690 47      1   0.999  1.000   1.000
1691 47      1   0.999  1.000   1.000
1692 47      1   0.999  1.000   1.000
1693 47      1   0.999  1.000   1.000
1694 47      1   0.999  1.000   1.000
1695 48      1   1.000  1.000   1.000
1696 48      1   1.000  1.000   1.000
1697 48      1   1.000  1.000   1.000
1698 48      1   1.000  1.000   1.000
1699 48      1   1.000  1.000   1.000
1700 48      1   1.000  1.000   1.000
1701 48      1   1.000  1.000   1.000
1702 48      1   1.000  1.000   1.000
1703 49      1   1.000  1.000   1.000
1704 49      1   1.000  1.000   1.000
1705 49      1   1.000  1.000   1.000
1706 49      1   1.000  1.000   1.000
1707 49      1   1.000  1.000   1.000
1708 49      1   1.000  1.000   1.000
1709 49      1   1.000  1.000   1.000
1710 49      1   1.000  1.000   1.000
1711 49      1   1.000  1.000   1.000
1712 50      1   1.000  1.000   1.000
1713 50      1   1.000  1.000   1.000
1714 50      1   1.000  1.000   1.000
1715 51      1   1.000  1.000   1.000
1716 51      1   1.000  1.000   1.000
1717 51      1   1.000  1.000   1.000
1718 51      1   1.000  1.000   1.000
1719 51      1   1.000  1.000   1.000
1720 51      1   1.000  1.000   1.000
1721 51      1   1.000  1.000   1.000
1722 53      1   1.000  1.000   1.000
1723 53      1   1.000  1.000   1.000
1724 54      1   1.000  1.000   1.000
1725 54      1   1.000  1.000   1.000
1726 55      1   1.000  1.000   1.000
1727 56      1   1.000  1.000   1.000
1728 56      1   1.000  1.000   1.000
1729 57      1   1.000  1.000   1.000
1730 58      1   1.000  1.000   1.000
1731 59      1   1.000  1.000   1.000
1732 62      1   1.000  1.000   1.000
1733 63      1   1.000  1.000   1.000

sizeMat documentation built on Aug. 1, 2019, 1:05 a.m.