Download Accelerated Life Models: Modeling and Statistical Analysis by Vilijandas Bagdonavicius, Mikhail Nikulin PDF

By Vilijandas Bagdonavicius, Mikhail Nikulin

The authors of this monograph have built a wide and critical type of survival research types that generalize many of the present versions. In a unified, systematic presentation, this monograph absolutely info these versions and explores parts of sped up existence checking out often purely touched upon within the literature.Accelerated existence versions: Modeling and Statistical research offers types, equipment of knowledge assortment, and statistical research for failure-time regression facts in speeded up existence trying out and for degradation info with explanatory variables. as well as the classical effects, the authors commit enormous awareness to versions with time-varying explanatory variables and to equipment of semiparametric estimation. in addition they learn the simultaneous research of deterioration and failure-time information while the intensities of failure in several modes rely on the extent of decay and the values of explanatory variables.The authors stay away from technical info by way of explaining the guidelines and concerning assets the place thorough research are available. no matter if used for instructing, learn or normal reference, speeded up existence types: Modeling and Statistical research presents new and recognized versions and glossy tools of speeded up lifestyles information research.

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Extra resources for Accelerated Life Models: Modeling and Statistical Analysis

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Suppose that both the PH and the AFT models hold on E. 14 implies for all x ∈ E1 α t θ(x) Sx (t) = exp − . 59) Set θi = θ(xi ), i = 1, 2. Then Sxi (t) = exp − t θi α , αxi (t) = α α−1 t . 60) The PH model implies αxs (·) (t) = αx1 (t), αx2 (t), 0 < t < s, t ≥ s, and for all t > s t Sxs (·) (t) = exp{− 0 s αxs (·) (u)du} = exp{− 0 αx1 (u)du − t s αx2 (u)du} = 36 ACCELERATED LIFE MODELS α s θ1 exp − α t θ2 − + s θ2 α . 62) imply that for all t > s s θ1 α + α t θ2 − s θ2 α =− s t−s + θ1 θ2 α . 63) If α = 1, this equality is verified.

2. 30)   where 0, Tx(·) < tk−1 , Tx(·) − tk−1 , tk−1 ≤ Tx(·) < tk ,  Tx(·) ≥ tk , tk − tk−1 , is the life in the interval [tk−1 , tk ) for the unit tested under the stress x(·). 25) implies that for tx(·) (p) ∈ [tk−1 , tk ) the following equality holds: k−1 tx(·) (p) − tk−1 ti − ti−1 + = 1. 31) is the model of Peshes-Stepanova (see, Kartashov, 1979). 31) are implied by the AFT model and illustrate various properties of this model. 31) can be written in the form tx(·) (p) − t1 t1 + = 1. tx1 (p) tx2 (p) So E(Tx1 ) = and tx1 (p) = 1− E(T1 ) 1− t1 tx(·) (p)−t1 tx2 (p) E(T2 ) E(Tx2 ) , , if tx(·) (p) ≥ t1 .

Proof. Set a = Ax1 (t1 ) = Ax(·) (t1 ) = Ax2 (t∗1 ). 2) implies that the cumulative hazard satisfies the integral equation t Ax(·) (t) = 0 g x(u), Ax(·) (u) du. 9) imply that for all t ≥ t1 t Ax(·) (t) = a + and Ax2 (t − t1 + t∗1 ) = a + t1 t t1 g x2 , Ax(·) (u) du g (x2 , Ax2 (u − t1 + t∗1 )) du. So for all t ≥ t1 the functions Ax(·) (t) and Ax2 (t − t1 + t∗1 ) satisfy the integral equation t h(t) = a + t1 g (x2 , h(u)) du with the initial condition h(t1 ) = a. The solution of this equation is unique, therefore we have Ax(·) (t) = Ax2 (t − t1 + t∗1 ), for all t ≥ t1 .

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