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Lalita Singh

Publications and source records attributed to Lalita Singh.

2 recordsLinked to original sources

The LR1 Lifetime Distribution: Properties, Nonmonotone Hazard, and Statistical Inference

The LR1 distribution links an exponential lifetime and a four-stage gamma lifetime through a single positive parameter $λ$. Their rates, $2λ$ and $λ/2$, have a fixed ratio, whereas the exponential mixing probability $λ^2/(1+λ^2)$ changes with the parameter. This restriction produces a hazard that decreases near zero and eventually increases toward $λ/2$ for every $λ>0$. We establish this behavior analytically and obtain an explicit parameter threshold separating decreasing densities from densities with an interior local peak. Distributional calculations provide survival probabilities, moments, transforms, truncated moments, quantiles, order statistics, and reliability summaries. The density at zero establishes identifiability, and strict decrease of the mean ensures a unique moment estimate for every positive sample mean. Likelihood inference includes the score, observed information, a constrained expectation--maximization algorithm, and asymptotic confidence limits; spacing estimation and the likelihood under independent right censoring are also described. Eight Monte Carlo settings, comprising 4,000 generated datasets, quantify the error of likelihood and moment estimators and the coverage of log-scale intervals. The results apply in a fixed working time unit and concern mathematical properties and correctly specified simulation, rather than demonstrated superiority on observed data.

stat.ME↗

The LR2 Lifetime Distribution: Rate Crossing, Reliability Properties, and Estimation

We study the LR2 one-parameter lifetime distribution obtained by mixing an exponential component of rate $θ/2$ and a gamma component with shape four and rate $θ^2$. The exponential mixing probability is $θ^2/(1+θ^2)$ for $θ>0$. We derive the density, survival function, moments, transforms, truncated moments, quantiles, order-statistic distributions, mean residual life, and stress--strength reliability. Identifiability follows from the density at the origin, and strict monotonicity of the mean yields a unique moment estimator. A complete density-turning-point criterion and analytic initial and tail hazard expansions clarify the possible shapes. The component rates cross at one half. The hazard decreases initially for every positive parameter and eventually increases in the gamma-dominated regime; it eventually decreases in the exponential-dominated regime. We develop likelihood estimation, observed information, constrained expectation--maximization, spacing estimation, and inference under regularity conditions, and state the likelihood for independent right censoring. A reproducible Monte Carlo study with eight settings and 4,000 generated samples compares likelihood and moment estimation and evaluates log-scale confidence intervals. The analysis distinguishes mathematical properties from empirical validation and explains the restrictions associated with a fixed working time unit.

stat.ME↗