Loglogsurvival: Survival related functions for the Loglog distribution

In reliaR: Package for some probability distributions.

Description

Conditional reliability function (crf), hazard function, hazard rate average (HRA) and survival function for the Loglog distribution with shape parameter alpha and scale parameter lambda.

Usage

crf.loglog(x, t = 0, alpha, lambda)
hloglog(x, alpha, lambda)
hra.loglog(x, alpha, lambda)
sloglog(x, alpha, lambda)

Arguments

x	vector of quantiles.
alpha	shape parameter.
lambda	scale parameter.
t	age component.

Value

crf.loglog gives the conditional reliability function (crf), hloglog gives the hazard function, hra.loglog gives the hazard rate average (HRA) function, and sloglog gives the survival function for the Loglog distribution.

References

Pham, H.(2002). A Vtub-Shaped Hazard Rate Function with Applications to System Safety, International Journal of Reliability and Applications. ,Vol. 3, No. l, pp. 1-16.

Pham, H.(2006). System Software Reliability, Springer-Verlag.

See Also

dloglog for other Loglog(Pham) distribution related functions;

Examples

## load data set 
data(sys2)
## Maximum Likelihood(ML) Estimates of alpha & lambda for the data(sys2)
## alpha.est = 0.9058689 lambda.est = 1.0028228

## Reliability indicators for data(sys2):

## Reliability function
sloglog(sys2, 0.9058689, 1.0028228)

## Hazard function 
hloglog(sys2, 0.9058689, 1.0028228)

## hazard rate average(hra)
hra.loglog(sys2, 0.9058689, 1.0028228)

## Conditional reliability function (age component=0)
crf.loglog(sys2, 0.00, 0.9058689, 1.0028228)

## Conditional reliability function (age component=3.0)
crf.loglog(sys2, 3.0, 0.9058689, 1.0028228)

Example output

 [1] 0.98834928 0.98261778 0.97685490 0.96573813 0.94590669 0.94125739
 [7] 0.92851483 0.91773568 0.91564208 0.91261035 0.91053066 0.88821180
[13] 0.88013059 0.86017764 0.84856815 0.81717718 0.81498574 0.81050087
[19] 0.80090312 0.78881220 0.78188163 0.74705253 0.74032921 0.73512075
[25] 0.72894205 0.72082220 0.71663681 0.71117119 0.70334954 0.69422122
[31] 0.69011640 0.67101759 0.65909592 0.65602060 0.63286797 0.61039819
[37] 0.60626096 0.59420878 0.58576056 0.55036279 0.55029681 0.54833269
[43] 0.53480188 0.50355339 0.49777470 0.49072502 0.47691995 0.47158560
[49] 0.46037624 0.40846550 0.40047644 0.39846525 0.38217987 0.37402635
[55] 0.34113963 0.32007244 0.31150276 0.29228609 0.27877966 0.27378351
[61] 0.26944995 0.26426277 0.24916122 0.24844963 0.22544290 0.22377245
[67] 0.20947987 0.20582801 0.19500213 0.16570022 0.15677674 0.15054697
[73] 0.12001734 0.11240440 0.09715929 0.08572282 0.07730341 0.06504950
[79] 0.06270877 0.05669037 0.04585064 0.04318116 0.04259810 0.03984360
[85] 0.03765825 0.02997229
 [1] 0.002229217 0.002150728 0.002099738 0.002038396 0.001982838 0.001975080
 [7] 0.001960009 0.001952552 0.001951544 0.001950305 0.001949598 0.001948065
[13] 0.001949724 0.001957609 0.001964256 0.001988153 0.001990099 0.001994183
[19] 0.002003359 0.002015717 0.002023178 0.002064465 0.002073114 0.002079956
[25] 0.002088233 0.002099367 0.002105219 0.002112975 0.002124297 0.002137837
[31] 0.002144041 0.002173824 0.002193180 0.002198268 0.002237831 0.002278369
[37] 0.002286067 0.002308913 0.002325306 0.002397503 0.002397643 0.002401822
[43] 0.002431114 0.002502310 0.002516045 0.002533053 0.002567184 0.002580674
[49] 0.002609588 0.002754449 0.002778507 0.002784645 0.002835592 0.002861971
[55] 0.002974881 0.003053342 0.003086800 0.003165406 0.003223894 0.003246267
[61] 0.003266012 0.003290077 0.003362976 0.003366521 0.003487046 0.003496276
[67] 0.003578220 0.003600063 0.003667187 0.003869598 0.003938439 0.003988868
[73] 0.004270766 0.004352272 0.004533517 0.004689199 0.004817673 0.005032057
[79] 0.005077561 0.005202811 0.005466082 0.005540456 0.005557309 0.005640165
[85] 0.005710065 0.005992761
 [1] 0.002446581 0.002353699 0.002291306 0.002212092 0.002130703 0.002117476
 [7] 0.002088089 0.002069073 0.002065864 0.002061458 0.002058592 0.002034410
[13] 0.002028033 0.002016283 0.002011575 0.002004760 0.002004553 0.002004225
[19] 0.002003929 0.002004284 0.002004823 0.002010755 0.002012452 0.002013878
[25] 0.002015690 0.002018266 0.002019677 0.002021602 0.002024516 0.002028145
[31] 0.002029854 0.002038422 0.002044261 0.002045827 0.002058371 0.002071783
[37] 0.002074382 0.002082181 0.002087849 0.002113379 0.002113430 0.002114931
[43] 0.002125518 0.002151620 0.002156705 0.002163019 0.002175747 0.002180795
[49] 0.002191646 0.002246457 0.002255608 0.002257945 0.002277356 0.002287417
[55] 0.002330516 0.002360466 0.002373229 0.002403185 0.002425440 0.002433943
[61] 0.002441444 0.002450579 0.002478208 0.002479550 0.002525067 0.002528544
[67] 0.002559358 0.002567554 0.002592693 0.002668054 0.002693529 0.002712139
[73] 0.002815376 0.002844975 0.002910398 0.002966164 0.003011891 0.003087622
[79] 0.003103605 0.003147440 0.003238834 0.003264475 0.003270274 0.003298730
[85] 0.003322664 0.003418798
 [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[39] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[77] 1 1 1 1 1 1 1 1 1 1
 [1] 0.9614356 0.9747080 0.9820138 0.9895124 0.9953749 0.9961750 0.9978230
 [8] 0.9988059 0.9989664 0.9991845 0.9993250 1.0004868 1.0007941 1.0013891
[15] 1.0016570 1.0021950 1.0022250 1.0022839 1.0023998 1.0025289 1.0025956
[22] 1.0028673 1.0029100 1.0029413 1.0029766 1.0030202 1.0030414 1.0030681
[29] 1.0031043 1.0031436 1.0031603 1.0032316 1.0032711 1.0032808 1.0033468
[36] 1.0034014 1.0034106 1.0034359 1.0034525 1.0035131 1.0035132 1.0035162
[43] 1.0035357 1.0035753 1.0035818 1.0035895 1.0036036 1.0036088 1.0036191
[50] 1.0036591 1.0036642 1.0036655 1.0036751 1.0036796 1.0036956 1.0037043
[57] 1.0037074 1.0037139 1.0037180 1.0037194 1.0037206 1.0037219 1.0037255
[64] 1.0037257 1.0037303 1.0037306 1.0037329 1.0037334 1.0037348 1.0037375
[71] 1.0037380 1.0037382 1.0037383 1.0037380 1.0037369 1.0037357 1.0037344
[78] 1.0037322 1.0037316 1.0037302 1.0037269 1.0037260 1.0037258 1.0037247
[85] 1.0037238 1.0037200

reliaR documentation built on May 1, 2019, 9:51 p.m.