Description Usage Arguments Details Value Author(s) Examples
Generate random data set of weibull distributed failure time, covariates and corresponding censoring status with a given shape and a set of regression parameters. Correlated covariates can also be drawn with a given number of correlated covariates.
1 2 | data.weibull(n, shape = 2, regco = c(1, 3), rcen = 0.25, ncorvar = 3,
correlated = FALSE)
|
n |
sample size |
shape |
value of shape parameter |
regco |
vector of regression parameters that corresponds to covariates, for correlated = FALSE |
rcen |
censoring rate |
ncorvar |
no of correlated covariates, for correlated = TRUE. See details below. |
correlated |
logical; if true correlated covariates will be generated with a given no of correlated covariates |
ncorvar is non required if correlated = FALSE and regco is not required if correlated = TRUE.
Data frame with columns:
ftime |
lifetime data from weibull distribution |
x |
covariates |
delta |
censoring status, 0 or 1. A value 0 indicates corresponding observation is censored |
Mazharul Islam and Hasinur Rahaman Khan
1 2 3 | data.weibull(n = 20)
data.weibull(n = 20, shape=1.7, regco=c(2,1,3,4))
data.weibull(n = 20, shape=1.5, ncorvar=4, correlated=TRUE)
|
Loading required package: survival
Loading required package: MASS
ftime x1 x2 delta
1 5.5285051 0.01825500 0.76984909 1
2 1.6811140 0.24665820 0.11919649 1
3 3.2054426 0.58924707 0.61226851 1
4 4.1722637 0.67273321 0.52851914 1
5 5.0110929 0.30118537 0.89722350 1
6 2.6900875 0.75709108 0.21139642 1
7 2.8383086 0.74855660 0.76416580 1
8 3.1576081 0.09721157 0.74808237 0
9 2.9870133 0.71354583 0.65525743 1
10 4.2251690 0.47055266 0.93662024 1
11 3.8548061 0.09370593 0.56201747 0
12 4.9765836 0.42335303 0.94037335 1
13 1.4585501 0.50286922 0.06119989 0
14 7.5036330 0.24207294 0.94430023 1
15 3.1080147 0.48320021 0.27399907 1
16 3.0347549 0.76174261 0.65480418 1
17 1.2913088 0.26753738 0.20687737 1
18 1.7081739 0.12938265 0.03195374 1
19 0.6572288 0.48336809 0.06385313 1
20 2.5900849 0.70655513 0.82503060 1
ftime x1 x2 x3 x4 delta
1 1.7591574 0.48895197 0.51761414 0.94783679 0.12702849 1
2 7.3066656 0.33860026 0.10418987 0.83089183 0.47006116 1
3 5.6640033 0.91860804 0.76865910 0.06800085 0.29369470 1
4 11.8021209 0.83116912 0.87340684 0.12005294 0.93947178 0
5 5.8346460 0.23754037 0.91648091 0.07708892 0.73645608 0
6 5.5170374 0.53142018 0.25102757 0.48899650 0.56631368 0
7 4.9772100 0.34814745 0.31923140 0.56896707 0.72724784 1
8 2.9762220 0.35510713 0.69555422 0.33111285 0.04525866 1
9 3.9826208 0.25005544 0.51062742 0.63474262 0.62464867 1
10 0.5291483 0.96667684 0.38975192 0.21265227 0.22315152 1
11 2.4060400 0.61877205 0.70149986 0.27306367 0.60447994 1
12 11.6563045 0.72048235 0.74638697 0.25999403 0.08771913 1
13 10.2811909 0.03729592 0.99167551 0.71759676 0.98862901 1
14 3.8653466 0.66801935 0.97248495 0.21415337 0.20270901 1
15 1.3593653 0.02073816 0.32865457 0.33824482 0.19675015 1
16 14.5608605 0.83454387 0.26738802 0.50591333 0.97270514 1
17 8.8231974 0.68289613 0.59220147 0.52443549 0.62242043 1
18 3.3848888 0.64392464 0.04399232 0.39001369 0.82313560 0
19 4.3990387 0.38945267 0.34275350 0.59909000 0.19967283 1
20 1.4605024 0.61379839 0.36641330 0.12751954 0.98288194 1
ftime x1 x2 x3 x4 delta
1 22.7575066 5.979719 5.791697 5.490143 4.961273 1
2 11.0640008 6.103569 5.633859 5.966207 5.396877 1
3 4.9277428 3.197703 3.936553 2.908292 4.327912 0
4 37.2995514 4.963802 4.885824 4.122696 3.938070 0
5 14.5305134 4.727272 3.540627 4.402988 4.809045 1
6 18.0983987 3.147721 4.578854 3.875326 2.677945 1
7 7.7780033 6.159772 5.812586 5.240550 4.898950 1
8 34.0687087 4.077360 3.670701 4.518825 3.968879 0
9 9.5602195 5.583241 5.284334 4.361992 4.695983 1
10 19.3382165 3.554495 3.814267 3.659040 3.279019 0
11 8.2993946 3.804916 4.783440 4.298398 4.799240 1
12 0.6835952 4.381773 4.657757 3.582894 4.405798 1
13 15.3102565 5.276127 4.825016 4.536843 5.553946 1
14 11.3650201 4.945651 5.494872 5.320811 5.945011 0
15 11.6018515 3.599004 3.515798 3.333251 3.929236 1
16 45.3525173 3.921258 3.485051 5.084968 4.308731 1
17 5.6228149 5.163803 4.495212 5.023717 4.032901 1
18 42.5102139 4.217659 4.978060 4.117231 6.000722 1
19 11.1442800 5.544063 5.534483 5.323767 4.532580 1
20 41.9696700 6.254060 6.303641 5.155098 5.842869 1
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