The Beta Type I Generalized Half Logistic Distribution: Properties and Application

Abstract

In a view to obtain a new distribution that is more exible than the type I generalized half logistic distribution, we used the beta-G generator and the type I generalized half logistic distribution. Some properties of the new distribution including the cummulative distribution function,survival function, hazard function were studied. Estimation of parameters were done using the maximum likelihood estimation method. Application of the derived distribution to lifetime data was illustrated by applying to remission times of bladder cancer patient data and survival times of guinea pigs.

Inference on the Beta Type I Generalized Half Logistic Distribution Under Right Censored Observation with Application to Covid-19

“…After analysis, Figure 1 shows the histogram of the survival times of the patients, with the fit of the BTIGHLD. It reveals that the data are rightly skewed which from [14] had shown that the BTIGHLD can give good fit.…”

“…A further study on some of the properties and estimation of the parameter of distribution of under complete observation was carried out by [13]. e author of [14] extended the distribution of [8] by addition of a parameter to have the Lehmann type II generalized half logistic distribution. Due to the nondecreasing properties of the hazard function of the type I generalized half logistic distribution, e author of [15] derived the BTIGHLD that is not limited to only nondecreasing hazards but can take any other form of hazard function.…”

“…e author of [14] extended the distribution of [8] by addition of a parameter to have the Lehmann type II generalized half logistic distribution. Due to the nondecreasing properties of the hazard function of the type I generalized half logistic distribution, e author of [15] derived the BTIGHLD that is not limited to only nondecreasing hazards but can take any other form of hazard function. Its properties were studied and estimation of parameters was done under complete observations.…”

“…In literature, several studies have been conducted to examine other generalizations of the half logistic distribution under incomplete data situations. Some of these include [4][5][6][7][8][9][10][11][12][13][14][15][16]. e author of [16] obtained an extended generalized half logistic distribution and studied different methods of estimation of its parameters based on censored and complete data, In this paper, we examined some statistical properties of the beta type I generalized half logistic and study its inferences under right-censored observations.…”

The Beta Power Muth Distribution: Regression Modeling, Properties and Data Analysis

“…The first data set is given by Aarset (1987) and represents the time to first failure of 50 devices (in weeks). This data set is: 0.1, 0.2, 1, 1, 1, 1, 1, 2, 3,6,7,11,12,18,18,18,18,18,21,32,36,40,45,46,47,50,55,60,63,63,67,67,67,67,72,75,79,82,82,83,84,84,84,85,85,85,85,85,86,86. The TTT-plot of this data set, in Figure 3(a), shows a convex shape followed by a concave shape.…”