scholarly journals A Notable Bounded Probability Distribution for Environmental and Lifetime Data

2021 ◽  
Author(s):  
Hassan Bakouch ◽  
Tassaddaq Hussain ◽  
Christophe Chesneau ◽  
Jónás Tamás
Keyword(s):  
Probability Distribution ◽  
Return Period ◽  
Annual Rainfall ◽  
Lifetime Data ◽  
Lindley Distribution ◽  
Rainfall Analysis ◽  
Gamma Distributions ◽  
Proposed Model ◽  
Competing Models ◽  
Points Of View

Abstract In this article, we introduce a notable bounded distribution based on a modification of the epsilon function which creates an upper bound on the domain of the distribution. Further, a key feature of the distribution links the readers with the asymptotic connections with the famous Lindley distribution, which is a weighted variant of the exponential distribution and also a mixture of exponential and gamma distributions. In some ways, the proposed distribution provides a flexible solution to the modeling of bounded characteristics that can be almost well-fitted by the Lindley distribution if the domain is restricted. Moreover, we have also explored its application, particularly with reference to lifetime and environmental points of view, and found that the proposed model exhibits a better fit among the competing models. Further, from the annual rainfall analysis, the proposed model exhibits a realistic return period of the rainfall.

scholarly journals On a new generalized lindley distribution: Properties, estimation and applications

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0244328
Author(s):  
Ali Algarni
Keyword(s):  
Asymptotic Variance ◽  
Real Data ◽  
Lifetime Data ◽  
Unknown Parameters ◽  
Data Set ◽  
Lindley Distribution ◽  
New Family ◽  
Proposed Model ◽  
The Subject ◽  
Mean Square Error Criterion

In this study, an extension of the generalized Lindley distribution using the Marshall-Olkin method and its own sub-models is presented. This new model for modelling survival and lifetime data is flexible. Several statistical properties and characterizations of the subject distribution along with its reliability analysis are presented. Statistical inference for the new family such as the Maximum likelihood estimators and the asymptotic variance covariance matrix of the unknown parameters are discussed. A simulation study is considered to compare the efficiency of the different estimators based on mean square error criterion. Finally, a real data set is analyzed to show the flexibility of our proposed model compared with the fit attained by some other competitive distributions.

scholarly journals New class of Lindley distributions: properties and applications

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Duha Hamed ◽  
Ahmad Alzaghal
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Simulation Study ◽  
Likelihood Estimation ◽  
Statistical Properties ◽  
Data Sets ◽  
Lifetime Data ◽  
Unknown Parameters ◽  
Lindley Distribution ◽  
New Class

AbstractA new generalized class of Lindley distribution is introduced in this paper. This new class is called the T-Lindley{Y} class of distributions, and it is generated by using the quantile functions of uniform, exponential, Weibull, log-logistic, logistic and Cauchy distributions. The statistical properties including the modes, moments and Shannon’s entropy are discussed. Three new generalized Lindley distributions are investigated in more details. For estimating the unknown parameters, the maximum likelihood estimation has been used and a simulation study was carried out. Lastly, the usefulness of this new proposed class in fitting lifetime data is illustrated using four different data sets. In the application section, the strength of members of the T-Lindley{Y} class in modeling both unimodal as well as bimodal data sets is presented. A member of the T-Lindley{Y} class of distributions outperformed other known distributions in modeling unimodal and bimodal lifetime data sets.

Positive Mood as a Mediator of the Relations among Musical Preference, Postconsumption Product Evaluation, and Consumer Satisfaction

2007 ◽  
Vol 100 (3) ◽  
pp. 927-938 ◽  
Author(s):  
Ching-I Teng ◽  
Hsu-Min Tseng ◽  
Heng-Hui Wu
Keyword(s):  
Consumer Satisfaction ◽  
Structural Equation ◽  
Positive Mood ◽  
Product Evaluation ◽  
Equation Model ◽  
Coffee Shop ◽  
Chi Square ◽  
Musical Preference ◽  
Proposed Model ◽  
Competing Models

This study of how positive mood mediates the influences of musical preference and postconsumption product evaluation on consumer satisfaction focuses specifically on a model in which positive mood fully mediates the influences. The proposed model is compared with two competing models, and a structural equation model is used to test and compare the three theory-driven models. This study sampled 247 students majoring in management at a single university. They had mean age of 23 yr. ( SD = 2.5). This study used questionnaires to measure subjects' evaluations of a cup of coffee, preference for the music broadcast in the coffee shop, positive mood, and satisfaction after they had the coffee. Analysis indicated that the proposed model outperformed the two competing models in describing the data using chi-square difference tests. Positive mood was identified as a full mediator of the relationship between musical preference and consumer satisfaction. Moreover, the results demonstrate for service managers the importance of creating positive consumer mood.

Determinants of spatial variation in fire return period in a semiarid African savanna

2011 ◽  
Vol 20 (4) ◽  
pp. 540 ◽  
Author(s):  
T. G. O'Connor ◽  
C. M. Mulqueeny ◽  
P. S. Goodman
Keyword(s):  
Spatial Variation ◽  
Return Period ◽  
Vegetation Type ◽  
Fire Frequency ◽  
Fuel Load ◽  
Annual Rainfall ◽  
Vegetation Types ◽  
Terrestrial Vegetation ◽  
African Savanna ◽  
Data Set

Fire pattern is predicted to vary across an African savanna in accordance with spatial variation in rainfall through its effects on fuel production, vegetation type (on account of differences in fuel load and in flammability), and distribution of herbivores (because of their effects on fuel load). These predictions were examined for the 23 651-ha Mkuzi Game Reserve, KwaZulu-Natal, based on a 37-year data set. Fire return period varied from no occurrence to a fire every 1.76 years. Approximately 75% of the reserve experienced a fire approximately every 5 years, 25% every 4.1–2.2 years and less than 1% every 2 years on average. Fire return period decreased in relation to an increase in mean annual rainfall. For terrestrial vegetation types, median fire return periods decreased with increasing herbaceous biomass, from forest that did not burn to grasslands that burnt every 2.64 years. Fire was absent from some permanent wetlands but seasonal wetlands burnt every 5.29 years. Grazer biomass above 0.5 animal units ha–1 had a limiting influence on the maximum fire frequency of fire-prone vegetation types. The primary determinant of long-term spatial fire patterns is thus fuel load as determined by mean rainfall, vegetation type, and the effects of grazing herbivores.

scholarly journals Analyses of flood peak discharge in Cimadur river basin, Banten Province, Indonesia

2021 ◽  
Vol 331 ◽  
pp. 08006
Author(s):  
Arniza Fitri ◽  
Muhammad Shubhi Nurul Hadie ◽  
Adelia Agustina ◽  
Dian Pratiwi ◽  
Susarman ◽  
...  
Keyword(s):  
River Basin ◽  
Return Period ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Rainfall Distribution ◽  
Flood Peak ◽  
Type Iii ◽  
Pearson Type ◽  
Catchment Areas ◽  
Peak Discharges

Cimadur river basin is one of the most important catchment areas in Lebak District, Banten Province. For the past few years, the catchment has experienced floods during the rainy season. The big issue of flooding has been recorded recently in December 2019 which has caused damage and negative impacts to the local people and surrounding community. This study aims to analyze the possibility of flood peak discharges in the catchment area of the Cimadur river. The flood discharges are calculated for 2, 5, 10, 25, 50, and 100 years return period based on the daily rainfall data from the year 2011 to 2020. The rainfall and land use data are obtained from PT Saeba Consultant. In this study, the hydrological analyses are including 1) analyses of average annual rainfall using the Thiessen method; 2) analyses of rainfall distribution and estimation of design rainfall by considering three methods involving: Log-Normal, Log Pearson Type III, and Gumbel Type 1; and 3) analyses of flood discharges by adopting Nakayasu Synthetic Hydrograph Unit (SHU). The rainfall distribution analyses show that the Log Pearson Type III provided the best fit. Based on the flood peak discharges analyses, the results show that the flood discharges for the 5, 10, 25, and 50 years return period in the Cimadur river basin are 470.71 m3/s, 560.16 m3/s, 698 m3/s, and 820.4 m3/s, respectively.

scholarly journals Rainfall trend analysis using Mann-Kendall and Sen’s slope estimator test in West Kalimantan

2021 ◽  
Vol 893 (1) ◽  
pp. 012006
Author(s):  
F Aditya ◽  
E Gusmayanti ◽  
J Sudrajat
Keyword(s):  
Climate Change ◽  
Rainfall Variability ◽  
Annual Rainfall ◽  
Sen’S Slope Estimator ◽  
West Kalimantan ◽  
Rainfall Analysis ◽  
Sen’S Slope ◽  
Rainfall Trends ◽  
Slope Estimator ◽  
The Impact

Abstract Climate change has been a prominent issue in the last decade. Climate change on a global scale does not necessarily have the same effect in different regions. Rainfall is a crucial weather element related to climate change. Rainfall trends analysis is an appropriate step in assessing the impact of climate change on water availability and food security. This study examines rainfall variations and changes at West Kalimantan, focusing on Mempawah and Kubu Raya from 2000-2019. The Mann-Kendall (MK) and Sen's Slope estimator test, which can determine rainfall variability and long-term monotonic trends, were utilized to analyze 12 rainfall stations. The findings revealed that the annual rainfall pattern prevailed in all locations. Mempawah region tends to experience a downward trend, while Kubu Raya had an upward trend. However, a significant trend (at 95% confidence level) was identified in Sungai Kunyit with a slope value of -33.20 mm/year. This trend indicates that Sungai Kunyit will become drier in the future. The results of monthly rainfall analysis showed that significant upward and downward trends were detected in eight locations. Rainfall trends indicate that climate change has occurred in this region.

scholarly journals Chemical–protein interaction extraction via Gaussian probability distribution and external biomedical knowledge

2020 ◽  
Vol 36 (15) ◽  
pp. 4323-4330 ◽  
Author(s):  
Cong Sun ◽  
Zhihao Yang ◽  
Leilei Su ◽  
Lei Wang ◽  
Yin Zhang ◽  
...  
Keyword(s):  
Probability Distribution ◽  
Protein Interactions ◽  
Local Structure ◽  
Relation Extraction ◽  
Biomedical Literature ◽  
Supplementary Information ◽  
Biomedical Knowledge ◽  
Proposed Model ◽  
Gaussian Probability Distribution ◽  
Extraction Performance

Abstract Motivation The biomedical literature contains a wealth of chemical–protein interactions (CPIs). Automatically extracting CPIs described in biomedical literature is essential for drug discovery, precision medicine, as well as basic biomedical research. Most existing methods focus only on the sentence sequence to identify these CPIs. However, the local structure of sentences and external biomedical knowledge also contain valuable information. Effective use of such information may improve the performance of CPI extraction. Results In this article, we propose a novel neural network-based approach to improve CPI extraction. Specifically, the approach first employs BERT to generate high-quality contextual representations of the title sequence, instance sequence and knowledge sequence. Then, the Gaussian probability distribution is introduced to capture the local structure of the instance. Meanwhile, the attention mechanism is applied to fuse the title information and biomedical knowledge, respectively. Finally, the related representations are concatenated and fed into the softmax function to extract CPIs. We evaluate our proposed model on the CHEMPROT corpus. Our proposed model is superior in performance as compared with other state-of-the-art models. The experimental results show that the Gaussian probability distribution and external knowledge are complementary to each other. Integrating them can effectively improve the CPI extraction performance. Furthermore, the Gaussian probability distribution can effectively improve the extraction performance of sentences with overlapping relations in biomedical relation extraction tasks. Availability and implementation Data and code are available at https://github.com/CongSun-dlut/CPI_extraction. Supplementary information Supplementary data are available at Bioinformatics online.

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