Generalised Skew Log Laplace Distribution

2021 ◽  
Author(s):  
Pradnya P. Khandeparkar ◽  
V. U. Dixit
Keyword(s):  
Laplace Distribution

Characterizations of Kumaraswamy Laplace Distribution with Applications

2016 ◽  
Vol 31 (2) ◽  
Author(s):  
Gokarna Aryal ◽  
Qiuming Zhang
Keyword(s):  
Recent Work ◽  
Laplace Distribution

AbstractIn this article we study a generalization of the Laplace distribution. The generalization is motivated by the recent work of Cordeiro and de Castro [

scholarly journals Forecasting The Exchange Rate Between Euro And USD: Probabilistic Approach Versus ARIMA And Exponential Smoothing Techniques

2012 ◽  
Vol 28 (2) ◽  
pp. 171 ◽  
Author(s):  
Paraschos Maniatis
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Probabilistic Approach ◽  
Laplace Distribution ◽  
Exponential Smoothing ◽  
Initial Time ◽  
Font Size ◽  
Smoothing Techniques ◽  
Initial Time Series ◽  
The Exchange Rate

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify; mso-pagination: none;" class="MsoNoSpacing"><span style="color: black; font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt; mso-themecolor: text1; mso-ansi-language: EN-US;">This study attempts to model the exchange rate between Euro and USD using univariate models- in particular ARIMA and exponential smoothing techniques. The time series analysis reveals non stationarity in data and, therefore, the models fail to give reliable predictions. However, differencing the initial time series the resulting series shows strong resemblance to white noise. The analysis of this series advocates independence in data and distribution satisfactorily close to Laplace distribution. The application of Laplace distribution offers reliable probabilities in forecasting changes in the exchange rate.</span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

scholarly journals Formulation of Measurement Sampling Plan for Small and Medium Batch Products in Supply Chain

2021 ◽  
Vol 14 ◽  
pp. 123-127
Author(s):  
Yuanpeng Sun
Keyword(s):  
Supply Chain ◽  
Laplace Distribution ◽  
Sampling Plan ◽  
Quality Characteristic ◽  
Discriminative Ability ◽  
Inspection Cost ◽  
Characteristic Data

The article studies the supply chain of suppliers and manufacturers, considering the overall benefits of the supply chain, the measurement sampling plan is the small batch sampling plan with the smallest amount of sampling and the strongest discriminative ability. If the quality characteristic data is a measurement value, and the inspection workload is large and the inspection cost is high, it is recommended to adopt the measurement sampling plan based on the Laplace distribution. On the premise of ensuring quality, try to reduce the number of inspected samples as much as possible to reduce the workload and cost of inspection.

scholarly journals Multiple Linear Regressions by Maximizing the Likelihood under Assumption of Generalized Gauss-Laplace Distribution of the Error

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Lorentz Jäntschi ◽  
Donatella Bálint ◽  
Sorana D. Bolboacă
Keyword(s):  
Normal Distribution ◽  
Linear Models ◽  
Linear Regression Analysis ◽  
Likelihood Estimation ◽  
Real Data ◽  
Multiple Linear Regression Analysis ◽  
Laplace Distribution ◽  
New Approach ◽  
Feature Information ◽  
Linear Regressions

Multiple linear regression analysis is widely used to link an outcome with predictors for better understanding of the behaviour of the outcome of interest. Usually, under the assumption that the errors follow a normal distribution, the coefficients of the model are estimated by minimizing the sum of squared deviations. A new approach based on maximum likelihood estimation is proposed for finding the coefficients on linear models with two predictors without any constrictive assumptions on the distribution of the errors. The algorithm was developed, implemented, and tested as proof-of-concept using fourteen sets of compounds by investigating the link between activity/property (as outcome) and structural feature information incorporated by molecular descriptors (as predictors). The results on real data demonstrated that in all investigated cases the power of the error is significantly different by the convenient value of two when the Gauss-Laplace distribution was used to relax the constrictive assumption of the normal distribution of the error. Therefore, the Gauss-Laplace distribution of the error could not be rejected while the hypothesis that the power of the error from Gauss-Laplace distribution is normal distributed also failed to be rejected.

The Laplace Distribution and Generalizations

2001 ◽  
Author(s):  
Samuel Kotz ◽  
Tomaz J. Kozubowski ◽  
Krzysztof Podgórski
Keyword(s):  
Laplace Distribution
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