A better approach to discuss medical science and engineering data with a modified Lehmann Type – II model

Abstract

Background: Modeling with the complex random phenomena that are frequently observed in reliability engineering, hydrology, ecology, medical science, and agricultural sciences was once thought to be an enigma. Scientists and practitioners agree that an appropriate but simple model is the best choice for this investigation. To address these issues, scientists have previously discussed a variety of bounded and unbounded, simple to complex lifetime models. Methods: We discussed a modified Lehmann type II (ML-II) model as a better approach to modeling bathtub-shaped and asymmetric random phenomena. A number of complementary mathematical and reliability measures were developed and discussed. Furthermore, explicit expressions for the moments, quantile function, and order statistics were developed. Then, we discussed the various shapes of the density and reliability functions over various model parameter choices. The maximum likelihood estimation (MLE) method was used to estimate the unknown model parameters, and a simulation study was carried out to evaluate the MLEs' asymptotic behavior. Results: We demonstrated ML- II's dominance over well-known competitors by modeling anxiety in women and electronic data.

A novel extended model with versatile shaped failure rate: Statistical inference with Covid -19 applications

“…We run thorough simulations to investigate behaviors of different estimators focussed on bias and mean squared error because it is tough to match characteristics of different estimation strategies theoretically. The new model is an excellent competitor with certain well-known and trendy models like two-parameter modified Kies inverted Topp-Leone (MKITL) [31] , modified Kies exponential (MKIEx) [32] , and NPF [16] distributions, according to the results of this study. In the future, we want to investigate a new MKIF distribution implementation designed on a reduced sample (check Sindhu et al.…”

“…Iqbal et al. [16] investigated a two-parameter model known as the new power function (NPF) model. The CDF and PDF of NPF model with scale and shape are The primary goal of this investigation is to create a flexible extremely versatile failure rate model known as the modified Kies new power function (MKNPF) model.…”

A comparative analysis of maximum likelihood estimation and artificial neural network modeling to assess electrical component reliability

“…In this part, we examine the implementation NPF model in engineering data. This data set is studied in detail by Iqbal et al 20 . They investigated at the lifespan (in days) of 30 electronic gadgets, with the following dataset: 0.020, 0.029, 0.044, 0.057, 0.034, 0.096, 0.139, 0.156, 0.106, 0.164, 0.177, 0.250, 0.326, 0.167, 0.607, 0.672, 0.650, 0.406, 0.736, 0.676, 0.817, 0.910, 0.931, 0.946, 0.838, 0.953, 0.961, 0.981, 0.982, 0.990.…”

A New Extended Model with Bathtub-Shaped Failure Rate: Properties, Inference, Simulation, and Applications

“…Iqbal et al [26] studied a two-parameter model called the new power function (NPF) distribution which is specified by the following CDF:…”

“…The type II censored ML estimators (CMLE)η CMLE , , and of the E-NPF distribution can be obtained by maximizing Equation (26) or by solving the above equations simultaneously by any numerical method as in Section 4.1.1.…”