Gompertzsurvival: Survival related functions for the Gompertz distribution

Description Usage Arguments Value References See Also Examples

Description

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

Usage

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crf.gompertz(x, t = 0, alpha, theta)
hgompertz(x, alpha, theta)
hra.gompertz(x, alpha, theta)
sgompertz(x, alpha, theta)

Arguments

x

vector of quantiles.

alpha

shape parameter.

theta

scale parameter.

t

age component.

Value

crf.gompertz gives the conditional reliability function (crf), hgompertz gives the hazard function, hra.gompertz gives the hazard rate average (HRA) function, and sgompertz gives the survival function for the Gompertz distribution.

References

Marshall, A. W., Olkin, I.(2007). Life Distributions: Structure of Nonparametric, Semiparametric, and Parametric Families, Springer, New York.

See Also

dgompertz for other Gompertz distribution related functions;

Examples

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## load data set
data(sys2)
## Maximum Likelihood(ML) Estimates of alpha & theta for the data(sys2)
## Estimates of alpha & theta using 'maxLik' package
## alpha.est = 0.00121307, theta.est = 0.00173329

## Reliability indicators for data(sys2):

## Reliability function
sgompertz(sys2, 0.00121307, 0.00173329)

## Hazard function
hgompertz(sys2, 0.00121307, 0.00173329)

## hazard rate average(hra)
hra.gompertz(sys2, 0.00121307, 0.00173329)

## Conditional reliability function (age component=0)
crf.gompertz(sys2, 0.00, 0.00121307, 0.00173329)

## Conditional reliability function (age component=3.0)
crf.gompertz(sys2, 3.0, 0.00121307, 0.00173329)

Example output

 [1] 0.99170794 0.98711223 0.98233343 0.97279740 0.95507764 0.95082609
 [7] 0.93902600 0.92889954 0.92691925 0.92404444 0.92206763 0.90063609
[13] 0.89279043 0.87325785 0.86180105 0.83054740 0.82835254 0.82385595
[19] 0.81421293 0.80202870 0.79502790 0.75968783 0.75283956 0.74752924
[25] 0.74122427 0.73293003 0.72865121 0.72306015 0.71505261 0.70569849
[31] 0.70148924 0.68188338 0.66962966 0.66646697 0.64263745 0.61948470
[37] 0.61521958 0.60279188 0.59407823 0.55755702 0.55748895 0.55546225
[43] 0.54150068 0.50926409 0.50330451 0.49603521 0.48180394 0.47630644
[49] 0.46475743 0.41134302 0.40313461 0.40106877 0.38434981 0.37598547
[55] 0.34229458 0.32075468 0.31200298 0.29240101 0.27864361 0.27355894
[61] 0.26915054 0.26387618 0.24853612 0.24781387 0.22449131 0.22280017
[67] 0.20834354 0.20465355 0.19372397 0.16421467 0.15525043 0.14899871
[73] 0.11844314 0.11084603 0.09566132 0.08429658 0.07594525 0.06381490
[79] 0.06150123 0.05555765 0.04487270 0.04224547 0.04167186 0.03896312
[85] 0.03681539 0.02927136
 [1] 0.001743391 0.001749025 0.001754912 0.001766746 0.001789046 0.001794458
 [7] 0.001809607 0.001822760 0.001825348 0.001829117 0.001831715 0.001860243
[13] 0.001870856 0.001897691 0.001913711 0.001958521 0.001961731 0.001968334
[19] 0.001982616 0.002000906 0.002011542 0.002066699 0.002077684 0.002086271
[25] 0.002096546 0.002110197 0.002117300 0.002126644 0.002140153 0.002156126
[31] 0.002163384 0.002197770 0.002219768 0.002225511 0.002269679 0.002314190
[37] 0.002322570 0.002347326 0.002364989 0.002441954 0.002442102 0.002446520
[43] 0.002477400 0.002551856 0.002566135 0.002583784 0.002619096 0.002633017
[49] 0.002662792 0.002810894 0.002835346 0.002841578 0.002893230 0.002919921
[55] 0.003033802 0.003112646 0.003146204 0.003224916 0.003283377 0.003305718
[61] 0.003325425 0.003349433 0.003422086 0.003425616 0.003545517 0.003554690
[67] 0.003636071 0.003657749 0.003724327 0.003924799 0.003992895 0.004042754
[73] 0.004321159 0.004401575 0.004580294 0.004733714 0.004860272 0.005071378
[79] 0.005116176 0.005239467 0.005498569 0.005571757 0.005588341 0.005669872
[85] 0.005738652 0.006016817
 [1] 0.001738335 0.001741146 0.001744079 0.001749965 0.001761021 0.001763697
 [7] 0.001771174 0.001777650 0.001778922 0.001780774 0.001782049 0.001796019
[13] 0.001801198 0.001814249 0.001822012 0.001843613 0.001845154 0.001848322
[19] 0.001855162 0.001863897 0.001868965 0.001895109 0.001900289 0.001904331
[25] 0.001909162 0.001915567 0.001918895 0.001923267 0.001929578 0.001937022
[31] 0.001940399 0.001956349 0.001966510 0.001969158 0.001989447 0.002009767
[37] 0.002013579 0.002024814 0.002032807 0.002067419 0.002067485 0.002069461
[43] 0.002083243 0.002116253 0.002122550 0.002130316 0.002145807 0.002151896
[49] 0.002164886 0.002228843 0.002239302 0.002241963 0.002263951 0.002275265
[55] 0.002323192 0.002356054 0.002369964 0.002402417 0.002426367 0.002435485
[61] 0.002443514 0.002453275 0.002482688 0.002484112 0.002532237 0.002535898
[67] 0.002568264 0.002576848 0.002603123 0.002681421 0.002707751 0.002726946
[73] 0.002832909 0.002863148 0.002929795 0.002986422 0.003032745 0.003109273
[79] 0.003125397 0.003169573 0.003261488 0.003287234 0.003293054 0.003321603
[85] 0.003345600 0.003441864
 [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] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
 [9] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
[17] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
[25] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
[33] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
[41] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
[49] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
[57] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
[65] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
[73] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646
[81] 1.003646 1.003646 1.003646 1.003646 1.003646 1.003646

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