Abstract
The toxicokinetic and toxicodynamic models (TK-TD) are very well-known for their ability, at both the individual and the population level, toВ accurately describe life cycles such as the growth, reproduction and survival of sentinel organisms under the influence of an ecological biomarker.В Being dynamics, the consistent inference of life history and environmental traits parameters that engender them is sometimes very complexВ numerically, especially as these parameters vary from oneВ individual to another. In this paper, we estimate the parameters of a survival modelВ TK-TD already applied and validated by the implementation of the R package GUTS (the General Unified Threshold Model of Survival) by anotherВ coding applied to another very recent implementation of Bayesian inference with the R package deBInfer in order to evaluate the survival effectsВ of our ecotoxicological biomarker called Deltamethrin on our Daphnia sample.В The study allowed us to evaluate from a population point of viewВ especially the threshold concentration not to be exceeded to observe a survival effect commonly known NEC (No effect Concentration) and possiblyВ determine the correlations between different variables of life history and the environment traits.
Highlights
Statistical methods for the analysis of survival data have continued to flourish over the last two decades [7], [31]
There is a diversity of toxicokinetic and toxicodynamic (TK-TD) models for modeling seemingly simple survival according to the underlying assumptions
The inference results are presented in tables In the third section (III) and IV
Summary
Statistical methods for the analysis of survival data have continued to flourish over the last two decades [7], [31]. There have been many publications that deal with this hot topic in various fields such as medicine [13], [19], [34], epidemiology [8], [21], criminology [7], [23], business reliability research [11], [29], [35], and the social and behavioral sciences [25], [27], [31], [36]. The General Unified Threshold Model for Survival (GUTS) is the more general survival TK-TD model from which a wide range of existing models can be inferred as special cases [17]. It has special cases of very appropriate model that can be adjusted to the survival data.
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