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Journal articles on the topic 'Mixture of lognormal distributions'

Author: Grafiati

Published: 18 April 2022

Last updated: 30 July 2025

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1

Liu, Z., J. Almhana, F. Wang, and R. Mcgorman. "Mixture Lognormal Approximations to Lognormal Sum Distributions." IEEE Communications Letters 11, no. 9 (2007): 711–13. http://dx.doi.org/10.1109/lcomm.2007.070656.

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Cao, Quang V., and Qinglin Wu. "Characterizing wood fiber and particle length with a mixture distribution and a segmented distribution." Holzforschung 61, no. 2 (2007): 124–30. http://dx.doi.org/10.1515/hf.2007.023.

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Abstract The length data from 12 samples of wood fibers and particles were described using lognormal and Weibull distributions. While both distributions fitted the middle range of the data well, the lognormal distribution provided a closer fit for short fibers and particles and the Weibull distribution was more appropriate for long ones. A mixture of the lognormal and Weibull distributions was developed using a variable weight to allow the new distribution to take the lognormal form for short fibers and gradually change to the Weibull form for long fibers. In the segmented distribution approac

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Areeak, Tidarut, and Tanatip Hanpayak. "MIXTURE DISTRIBUTION ANALYSIS OF DAIRY AVERAGE PM2.5 CONCENTRATIONS IN BANGKOK, THAILAND." Suranaree Journal of Science and Technology 31, no. 5 (2025): 030232(1–10). https://doi.org/10.55766/sujst-2024-05-e05095.

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Air pollution, specifically PM2.5, poses significant health risks and global environmental challenges. Bangkok, the capital city of Thailand, also experiences severe levels of PM2.5. The objective of this study is to determine the optimal probability distribution for PM2.5 concentration in Bangkok. Daily average PM2.5 concentrations from January 1, 2018, to December 31, 2022, were analyzed at 10 monitoring sites in the Bangkok area. The concentration patterns of PM2.5 were characterized using several statistical distributions, including lognormal, gamma, and Weibull distributions, as well as 2

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4

Kechejian, H., V. K. Ohanyan, and V. G. Bardakhchyan. "On Poisson Mixture of Lognormal Distributions." Lobachevskii Journal of Mathematics 41, no. 3 (2020): 340–48. http://dx.doi.org/10.1134/s1995080220030087.

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Cao, Quang V., and Thomas J. Dean. "Modeling Crown Structure from LiDAR Data with Statistical Distributions." Forest Science 57, no. 5 (2011): 359–64. http://dx.doi.org/10.1093/forestscience/57.5.359.

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Abstract The objective of this study was to evaluate the ability of three statistical distributions to characterize the vertical distribution of foliage mass in canopies of even-aged loblolly pine stands, based on airborne-scanning light detection and ranging (LiDAR) data. The functions were the Weibull and SB distributions and a mixture of the lognormal and Weibull distributions. Results indicated that the mixture distribution fit the LiDAR data better than the Weibull and SB distributions, according to three goodness-of-fit statistics. By switching from the lognormal for data near the tree t

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So, Jacky C. "The Distribution of Financial Ratios—A Note." Journal of Accounting, Auditing & Finance 9, no. 2 (1994): 215–23. http://dx.doi.org/10.1177/0148558x9400900205.

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Three competitive distributions are offered by the literature to explain the non-normality and skewness of the cross-sectional distribution of financial ratios: the mixture of normal distributions, the lognormal distribution, and the gamma distribution. Using a new technique, this paper shows that the lognormal distribution and the gamma distribution are not supported by the empirical evidence. Although these two distributions indeed capture skewness, they do not portray the correct shape of the distributions. The non-normal stable Paretian distribution seems to be good candidate to describe t

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Susanto, Irwan, and Sri Sulistijowati Handajani. "PENGELOMPOKAN RUMAH TANGGA DI INDONESIA BERDASARKAN PENDAPATAN PER KAPITA DENGAN MODEL FINITE MIXTURE." MEDIA STATISTIKA 13, no. 1 (2020): 13–24. http://dx.doi.org/10.14710/medstat.13.1.13-24.

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In the statistical modeling framework, the form of the income distribution can be approaching based on certain statistical distributions. The use of the finite mixture model is relatively flexible in the modeling of the income distribution that has a multimodal pattern. The multimodal pattern can be indicated as the existence of different cluster on the data. The different clusters which can reflect the economic homogeneity of income are represented by the mixture components of the finite mixture model. In this paper, the finite mixture model is implemented for modeling the distribution of hou

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Al-Moisheer, A. S. "Mixture of Lindley and Lognormal Distributions: Properties, Estimation, and Application." Journal of Function Spaces 2021 (December 28, 2021): 1–12. http://dx.doi.org/10.1155/2021/9358496.

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Finite mixture models provide a flexible tool for handling heterogeneous data. This paper introduces a new mixture model which is the mixture of Lindley and lognormal distributions (MLLND). First, the model is formulated, and some of its statistical properties are studied. Next, maximum likelihood estimation of the parameters of the model is considered, and the performance of the estimators of the parameters of the proposed models is evaluated via simulation. Also, the flexibility of the proposed mixture distribution is demonstrated by showing its superiority to fit a well-known real data set

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Brown, Simon, and David C. Simcock. "The Amoroso distribution as a model of the distribution of blood haemoglobin concentration." Deviot Institute Working Papers 2022 (January 3, 2022): 01. https://doi.org/10.5281/zenodo.7954065.

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The distribution of haemoglobin (Hb) concentration is often treated as though it is normal or lognormal, but the issue is frequently ignored. Part of the problem is that Hb concentration distribution can have negative, zero or positive skewness. To address this issue, we have shown previously that a normal mixture might be appropriate in some circumstances. Here we show that the Amoroso distribution is as good as or better than (a) the normal, lognormal, gamma, Weibull and skew normal distributions and (b) the normal mixture distribution used to describe Hb concentration. The Amoroso distribut

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Brown, Simon, and David C. Simcock. "On the distribution of blood haemoglobin concentration." Deviot Institute Working Papers 2021 (December 1, 2021): 02. https://doi.org/10.5281/zenodo.7951921.

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The distribution of blood haemoglobin (Hb) concentration is generally treated as though it is normal or lognormal, although the data are often negatively skewed, which is inconsistent with both distributions. The issue is complicated by the fact that the data are often edited to exclude biologically ‘implausible’ values and then to exclude biologically ‘abnormal’ values. This editing process tends to render the distribution more ‘statistically normal’, which, while convenient, prompts the concern that that might have been the desired outcome. Using the NHANE

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Bentzien, Sabrina, and Petra Friederichs. "Generating and Calibrating Probabilistic Quantitative Precipitation Forecasts from the High-Resolution NWP Model COSMO-DE." Weather and Forecasting 27, no. 4 (2012): 988–1002. http://dx.doi.org/10.1175/waf-d-11-00101.1.

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Abstract Statistical postprocessing is an integral part of an ensemble prediction system. This study compares methods used to derive probabilistic quantitative precipitation forecasts based on the high-resolution version of the German-focused Consortium for Small-Scale Modeling (COSMO-DE) time-lagged ensemble (COSMO-DE-TLE). The investigation covers the period from July 2008 to June 2011 for a region over northern Germany with rain gauge measurements from 445 stations. The investigated methods provide pointwise estimates of the predictive distribution using logistic and quantile regression, an

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C. A., Ugomma,. "On the Distribution of the Mixed-Lognormal-Weibull Option Pricing Model." Advanced Journal of Science, Technology and Engineering 4, no. 4 (2024): 111–24. http://dx.doi.org/10.52589/ajste-j50vxba8.

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This paper intends to test whether the Mixed-Lognormal-Weibull Distribution (MLWD) option pricing model comes from the same distribution and whether the model is a good fit in Black-Scholes option pricing model. The data for this study were obtained from Australian Clearing House of Australian Securities Exchange (ASX) which consist of 50 enlisted stock as products of monthly market summary for long term options collected from January, 3rd 2017 to December, 31st 2017, comprising 720 trading days arranged in accordance to 25, 27, 28, 29 and 30 maturity days. Maximum Likelihood Estimate was used

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Kidando, Emmanuel, Ren Moses, Eren E. Ozguven, and Thobias Sando. "Bayesian Nonparametric Model for Estimating Multistate Travel Time Distribution." Journal of Advanced Transportation 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/5069824.

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Multistate models, that is, models with more than two distributions, are preferred over single-state probability models in modeling the distribution of travel time. Literature review indicated that the finite multistate modeling of travel time using lognormal distribution is superior to other probability functions. In this study, we extend the finite multistate lognormal model of estimating the travel time distribution to unbounded lognormal distribution. In particular, a nonparametric Dirichlet Process Mixture Model (DPMM) with stick-breaking process representation was used. The strength of t

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Young, Virginia R. "Credibility Using Semiparametric Models." ASTIN Bulletin 27, no. 2 (1997): 273–85. http://dx.doi.org/10.2143/ast.27.2.542052.

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AbstractTo use Bayesian analysis to model insurance losses, one usually chooses a parametric conditional loss distribution for each risk and a parametric prior distribution to describe how the conditional distributions vary across the risks. A criticism of this method is that the prior distribution can be difficult to choose and the resulting model may not represent the loss data very well. In this paper, we apply techniques from nonparametric density estimation to estimate the prior. We use the estimated model to calculate the predictive mean of future claims given past claims. We illustrate

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Taylor, M., S. Kazadzis, and E. Gerasopoulos. "Multi-modal analysis of aerosol robotic network size distributions for remote sensing applications: dominant aerosol type cases." Atmospheric Measurement Techniques 7, no. 3 (2014): 839–58. http://dx.doi.org/10.5194/amt-7-839-2014.

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Abstract. To date, size distributions obtained from the aerosol robotic network (AERONET) have been fit with bi-lognormals defined by six secondary microphysical parameters: the volume concentration, effective radius, and the variance of fine and coarse particle modes. However, since the total integrated volume concentration is easily calculated and can be used as an accurate constraint, the problem of fitting the size distribution can be reduced to that of deducing a single free parameter – the mode separation point. We present a method for determining the mode separation point for equivalent

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Elmahdy, Emad E. "Modelling Reliability Data with Finite Weibull or Lognormal Mixture Distributions." Applied Mathematics & Information Sciences 11, no. 4 (2017): 1081–89. http://dx.doi.org/10.18576/amis/110414.

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Taylor, M., S. Kazadzis, and E. Gerasopoulos. "Multi-modal analysis of aerosol robotic network size distributions for remote sensing applications: dominant aerosol type cases." Atmospheric Measurement Techniques Discussions 6, no. 6 (2013): 10571–615. http://dx.doi.org/10.5194/amtd-6-10571-2013.

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Abstract. To date, size distributions obtained from the aerosol robotic network have been fit with bi-lognormals defined by six secondary microphysical parameters: the volume concentration, effective radius, and the variance of fine and coarse particle modes. However, since the total integrated volume concentration is easily calculated and can be used as an accurate constraint, the problem of fitting the size distribution can be reduced to that of deducing a single free parameter – the mode separation point. We present a method for determining the mode separation point for equivalent-volume bi

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18

Wang, H. Q., J. P. Dupont, R. Lafite, and R. Meyer. "A differentiation method for separating a mixture of suspended particle size distributions." Hydrology and Earth System Sciences 3, no. 2 (1999): 177–85. http://dx.doi.org/10.5194/hess-3-177-1999.

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Abstract. A simple method is proposed to partition a mixture of two populations in suspended particle size data. The method, termed here "the differentiation method" is based on the function of the lognormal distribution. Suspended material in marine or estuarine situations often consists of difficult-to-interpret complex populations. The treatment of particle size data by the method described enables the confirmation of the lognormal law and also the demonstration of the occurrence of a combination of a number of populations which may not be distinguished by the classical Gaussian transformat

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Sultan, K. S., and A. S. Al-Moisheer. "Mixture of Inverse Weibull and Lognormal Distributions: Properties, Estimation, and Illustration." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/526786.

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We discuss the two-component mixture of the inverse Weibull and lognormal distributions (MIWLND) as a lifetime model. First, we discuss the properties of the proposed model including the reliability and hazard functions. Next, we discuss the estimation of model parameters by using the maximum likelihood method (MLEs). We also derive expressions for the elements of the Fisher information matrix. Next, we demonstrate the usefulness of the proposed model by fitting it to a real data set. Finally, we draw some concluding remarks.

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Zhang, Lidong, Qikai Li, Yuanjun Guo, Zhile Yang, and Lei Zhang. "An Investigation of Wind Direction and Speed in a Featured Wind Farm Using Joint Probability Distribution Methods." Sustainability 10, no. 12 (2018): 4338. http://dx.doi.org/10.3390/su10124338.

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Wind direction and speed are both crucial factors for wind farm layout; however, the relationship between the two factors has not been well addressed. To optimize wind farm layout, this study aims to statistically explore wind speed characteristics under different wind directions and wind direction characteristics. For this purpose, the angular–linear model for approximating wind direction and speed characteristics were adopted and constructed with specified marginal distributions. Specifically, Weibull–Weibull distribution, lognormal–lognormal distribution and Weibull–lognormal distribution w

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Carrizosa, Emilio, Jelena Jocković, and Pepa Ramírez-Cobo. "A global optimisation approach for parameter estimation of a mixture of double Pareto lognormal and lognormal distributions." Computers & Operations Research 52 (December 2014): 231–40. http://dx.doi.org/10.1016/j.cor.2013.10.014.

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22

Marek, Lubos, and Michal Vrabec. "Wage Distribution Models." International Journal of Economics and Statistics 10 (March 15, 2022): 124–27. http://dx.doi.org/10.46300/9103.2022.10.19.

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In our article we try to contribute to the discussion of the possibility to predict the trend of the wage distribution. For this purpose we use data from Czech Republic. But our model is useable for all similar data types. Classical models use the probability distribution such as lognormal, Pareto, etc., but their results are not very good. We suggest using a mixture of normal probability distribution (normal mixture) in our model. We focus mainly on the possibility of constructing a mixture of normal distributions based on parameter estimation. We estimate these parameters on the basis of the

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23

Maaß, Sarah C., Joost de Jong, Leendert van Maanen, and Hedderik van Rijn. "Conceptually plausible Bayesian inference in interval timing." Royal Society Open Science 8, no. 8 (2021): 201844. http://dx.doi.org/10.1098/rsos.201844.

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In a world that is uncertain and noisy, perception makes use of optimization procedures that rely on the statistical properties of previous experiences. A well-known example of this phenomenon is the central tendency effect observed in many psychophysical modalities. For example, in interval timing tasks, previous experiences influence the current percept, pulling behavioural responses towards the mean. In Bayesian observer models, these previous experiences are typically modelled by unimodal statistical distributions, referred to as the prior. Here, we critically assess the validity of the as

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Kononenko, D. V. "Analysis of distributions of indoor radon concentrations in the regions of the Russian Federation." Radiatsionnaya Gygiena = Radiation Hygiene 12, no. 1 (2019): 85–103. http://dx.doi.org/10.21514/1998-426x-2019-12-1-85-103.

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During 2001–2017 more than 800 thousand records containing the results of measurements of radon concentration taken in 78 regions of Russia were accumulated in the Federal databank of radiation doses to the population of the Russian Federation. The paper presents the procedure and results of the first data analysis carried out to check the conformity of radon concentrations in the regions of Russia with the lognormal distribution and to calculate the parameters of these distributions. The procedure included verification and validation of data, plotting the frequency distribution histograms and

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Hengcharoensuk, Jiramet, and Adisak Moumeesri. "Ruin Probability Analysis in Automobile Insurance Using Gamma-Cubic Transmuted Exponential Distribution for Claim Severity." International Journal of Mathematical, Engineering and Management Sciences 10, no. 2 (2025): 486–505. https://doi.org/10.33889/ijmems.2025.10.2.024.

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Insurance companies must confront and manage financial risks to ensure their survival. This article analyzes and manages risks by estimating ruin probability using the newly developed Gamma-Cubic Transmuted Exponential (GCTE) claim severity distribution. The GCTE distribution is obtained by mixing distribution and Cubic Rank Transmuted map techniques. Its parameters are estimated using the maximum likelihood estimation (MLE) method. The performance of GCTE distribution is compared with well-known loss distributions such as Gamma, Weibull, Lognormal, Inverse Gaussian, mixture Lognormal, and the

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Thompson, Michael, Stephen L. R. Ellison, Linda Owen, et al. "Scoring in Genetically Modified Organism Proficiency Tests Based on Log-Transformed Results." Journal of AOAC INTERNATIONAL 89, no. 1 (2006): 232–39. http://dx.doi.org/10.1093/jaoac/89.1.232.

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Abstract The study considers data from 2 UK-based proficiency schemes and includes data from a total of 29 rounds and 43 test materials over a period of 3 years. The results from the 2 schemes are similar and reinforce each other. The amplification process used in quantitative polymerase chain reaction determinations predicts a mixture of normal, binomial, and lognormal distributions dominated by the latter 2. As predicted, the study results consistently follow a positively skewed distribution. Log-transformation prior to calculating z-scores is effective in establishing near-symmetric distrib

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Nyambega, Henry Ondicho. "Bayesian Estimation of Survivor Function for Censored Data Using Lognormal Mixture Distributions." IOSR Journal of Mathematics 13, no. 02 (2017): 19–32. http://dx.doi.org/10.9790/5728-1302041932.

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Kayano, Koichi, and Kunio Shimizu. "Optimal Thresholds for a Mixture of Lognormal Distributions as the Continuous Part of the Mixed Distribution." Journal of Applied Meteorology 33, no. 12 (1994): 1543–50. http://dx.doi.org/10.1175/1520-0450(1994)033<1543:otfamo>2.0.co;2.

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Zhang, Xu, Sean Barnes, Bruce Golden, Miranda Myers, and Paul Smith. "Lognormal-based mixture models for robust fitting of hospital length of stay distributions." Operations Research for Health Care 22 (September 2019): 100184. http://dx.doi.org/10.1016/j.orhc.2019.04.002.

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Nagode, Marko, Simon Oman, Jernej Klemenc, and Branislav Panić. "Finite Mixture Models: A Key Tool for Reliability Analyses." Mathematics 13, no. 10 (2025): 1605. https://doi.org/10.3390/math13101605.

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As system complexity increases, accurately capturing true system reliability becomes increasingly challenging. Rather than relying on exact analytical solutions, it is often more practical to use approximations based on observed time-to-failure data. Finite mixture models provide a flexible framework for approximating arbitrary probability density functions and are well suited for reliability modelling. A critical factor in achieving accurate approximations is the choice of parameter estimation algorithm. The REBMIX&EM algorithm, implemented in the rebmix R package, generally performs well

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Agterberg, F. P. "Mixtures of multiplicative cascade models in geochemistry." Nonlinear Processes in Geophysics 14, no. 3 (2007): 201–9. http://dx.doi.org/10.5194/npg-14-201-2007.

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Abstract. Multifractal modeling of geochemical map data can help to explain the nature of frequency distributions of element concentration values for small rock samples and their spatial covariance structure. Useful frequency distribution models are the lognormal and Pareto distributions which plot as straight lines on logarithmic probability and log-log paper, respectively. The model of de Wijs is a simple multiplicative cascade resulting in discrete logbinomial distribution that closely approximates the lognormal. In this model, smaller blocks resulting from dividing larger blocks into parts

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Valvo, Paolo S. "A Bimodal Lognormal Distribution Model for the Prediction of COVID-19 Deaths." Applied Sciences 10, no. 23 (2020): 8500. http://dx.doi.org/10.3390/app10238500.

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The paper presents a phenomenological epidemiological model for the description and prediction of the time trends of COVID-19 deaths worldwide. A bimodal distribution function—defined as the mixture of two lognormal distributions—is assumed to model the time distribution of deaths in a country. The asymmetric lognormal distribution enables better data fitting with respect to symmetric distribution functions. Besides, the presence of a second mode allows the model to also describe second waves of the epidemic. For each country, the model has six parameters, which are determined by fitting the a

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Khamees, Amr Khaled, Almoataz Y. Abdelaziz, Makram R. Eskaros, Mahmoud A. Attia, and Ahmed O. Badr. "The Mixture of Probability Distribution Functions for Wind and Photovoltaic Power Systems Using a Metaheuristic Method." Processes 10, no. 11 (2022): 2446. http://dx.doi.org/10.3390/pr10112446.

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The rising use of renewable energy sources, particularly those that are weather-dependent like wind and solar energy, has increased the uncertainty of supply in these power systems. In order to obtain considerably more accurate results in the analysis of power systems, such as in the planning and operation, it is necessary to tackle the stochastic nature of these sources. Operators require adequate techniques and procedures to mitigate the negative consequences of the stochastic behavior of renewable energy generators. Thus, this paper presents a modification of the original probability distri

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Krishnamoorthy, S., and B. Jaganathan. "CLUSTERING OF COUNT DATA USING POISSON DISTRIBUTION." Advances and Applications in Statistics 92, no. 8 (2025): 1183–200. https://doi.org/10.17654/0972361725053.

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Cluster analysis is often used to identify homogeneous groups within complex datasets, particularly when traditional distance-based methods struggle with high-dimensional or skewed data. In this study, we propose a model-based clustering approach for count data using a finite mixture of Poisson distributions. The model accounts for overdispersion and skewness, with parameters estimated via the expectation-maximization (EM) algorithm. Information criteria such as AIC and BIC are employed for model selection. A key novelty of this work lies in applying Poisson mixture models to a large-scale hea

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Allen, A. P., B. L. Li, and E. L. Charnov. "Population fluctuations, power laws and mixtures of lognormal distributions." Ecology Letters 4, no. 1 (2001): 1–3. http://dx.doi.org/10.1046/j.1461-0248.2001.00194.x.

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FOLTA, ZDENEK, PAVEL SKALNY, PETR MATEJKA, MIROSLAV TROCHTA, and DANIEL PISTACEK. "PROBABILISTIC ANALYSIS OF THE MAXIMAL LOAD OF INDUSTRIAL MACHINES." MM Science Journal 2021, no. 6 (2021): 5391–95. http://dx.doi.org/10.17973/mmsj.2021_12_2021106.

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This study describes the statistical analysis of peak forces of industrial washing machines. The data source comes from twelve different machines. The measurements are done using a force gauge installed in places for fastening screws. A new software based on LabView has been developed to gauge the acting forces. To determine extreme force values, various probability distributions are applied. Furthermore, a convex combination of lognormal distribution is used in more complicated cases. The parameters of the lognormal mixtures are determined using modified an Expectation-maximization algorithm.

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Kozlov, V. D., and A. I. Maysuradze. "Separation of a Mixture of Three-Parameter Lognormal Distributions in the Analysis of Communication Environments." Computational Mathematics and Modeling 30, no. 3 (2019): 311–19. http://dx.doi.org/10.1007/s10598-019-09457-8.

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Clarence Gray, David. "BAYESIAN MIXTURE APPROACH TO INCOME INEQUALITY AND POVERTY INDICES OF LIBERIA A STUDY USING HIES DATA OF 2016-2017." International Journal of Advanced Research 13, no. 04 (2025): 1234–49. https://doi.org/10.21474/ijar01/20835.

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This paper provides a generalized structure to evaluate income inequality and poverty, focusing on income distribution and applying a Bayesian approach to derive various poverty measures. A parametric model from income distribution and samples from the posterior distribution were used to formulate poverty indices. Explicitly, it scrutinizes the Foster Greer Thorbecke (FGT) poverty index which assesses poverty by incorporating its incidence, depth, and severity. We evaluate poverty using discrete and continuous FGT indices, applying a Bayesian mixture model with lognormal components in the libe

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Karal, Mohammad Abu Sayem, Nadia Akter Mokta, Victor Levadny, et al. "Effects of cholesterol on the size distribution and bending modulus of lipid vesicles." PLOS ONE 17, no. 1 (2022): e0263119. http://dx.doi.org/10.1371/journal.pone.0263119.

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The influence of cholesterol fraction in the membranes of giant unilamellar vesicles (GUVs) on their size distributions and bending moduli has been investigated. The membranes of GUVs were synthesized by a mixture of two elements: electrically neutral lipid 1, 2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) and cholesterol and also a mixture of three elements: electrically charged lipid 1,2-dioleoyl-sn-glycero-3-phospho-(1′-rac-glycerol) (DOPG), DOPC and cholesterol. The size distributions of GUVs have been presented by a set of histograms. The classical lognormal distribution is well fitted to

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He, Jiahang, and Toshiyuki Yamamoto. "Characterization of Daily Travel Distance of a University Car Fleet for the Purpose of Replacing Conventional Vehicles with Electric Vehicles." Sustainability 12, no. 2 (2020): 690. http://dx.doi.org/10.3390/su12020690.

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This study attempts to fit daily travel distances (DTD) data collected from the Nagoya University (NU) car-sharing system for one year to several distribution functions, including a lognormal mixture model. It is deemed here that the lognormal distribution performs best among the five tested single-distribution functions based on their p-values. Moreover, the lognormal mixture model can represent the driving pattern better overall with respect to the Akaike information criterion (AIC). Taking two types of electric vehicles (EVs) into consideration, the results show that 30 out of 48 vehicles c

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Malá, Ivana. "The Use of Finite Mixtures of Lognormal Distribution for the Modelling of Income Distributions." Acta Oeconomica Pragensia 20, no. 4 (2012): 26–39. http://dx.doi.org/10.18267/j.aop.373.

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Tan, Cher Ming, and Nagarajan Raghavan. "A bimodal three-parameter lognormal mixture distribution for electromigration failure analysis." Thin Solid Films 516, no. 23 (2008): 8804–9. http://dx.doi.org/10.1016/j.tsf.2008.06.078.

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Agrawal, Anand, and Rakhesh Singh Kshetrimayum. "Analysis of UWB communication over IEEE 802.15.3a channel by superseding lognormal shadowing by Mixture of Gamma distributions." AEU - International Journal of Electronics and Communications 69, no. 12 (2015): 1795–99. http://dx.doi.org/10.1016/j.aeue.2015.09.003.

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TAWEAB, FAUZIA ALI, NOOR AKMA IBRAHIM, and BADER AHMAD I. ALJAWADI. "ESTIMATION OF CURE FRACTION FOR LOGNORMAL RIGHT CENSORED DATA WITH COVARIATES." International Journal of Modern Physics: Conference Series 09 (January 2012): 308–15. http://dx.doi.org/10.1142/s2010194512005363.

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In clinical studies, a proportion of patients might be unsusceptible to the event of interest and can be considered as cured. The survival models that incorporate the cured proportion are known as cure rate models where the most widely used model is the mixture cure model. However, in cancer clinical trials, mixture model is not the appropriate model and the viable alternative is the Bounded Cumulative Hazard (BCH) model. In this paper we consider the BCH model to estimate the cure fraction based on the lognormal distribution. The parametric estimation of the cure fraction for survival data wi

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Cheema, Adnan Ahmad, and Sana Salous. "Spectrum Occupancy Measurements and Analysis in 2.4 GHz WLAN." Electronics 8, no. 9 (2019): 1011. http://dx.doi.org/10.3390/electronics8091011.

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High time resolution spectrum occupancy measurements and analysis are presented for 2.4 GHz WLAN signals. A custom-designed wideband sensing engine records the received power of signals, and its performance is presented to select the decision threshold required to define the channel state (busy/idle). Two sets of measurements are presented where data were collected using an omni-directional and directional antenna in an indoor environment. Statistics of the idle time windows in the 2.4 GHz WLAN are analyzed using a wider set of distributions, which require fewer parameters to compute and are m

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Corral, Álvaro, and Isabel Serra. "The Brevity Law as a Scaling Law, and a Possible Origin of Zipf’s Law for Word Frequencies." Entropy 22, no. 2 (2020): 224. http://dx.doi.org/10.3390/e22020224.

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An important body of quantitative linguistics is constituted by a series of statistical laws about language usage. Despite the importance of these linguistic laws, some of them are poorly formulated, and, more importantly, there is no unified framework that encompasses all them. This paper presents a new perspective to establish a connection between different statistical linguistic laws. Characterizing each word type by two random variables—length (in number of characters) and absolute frequency—we show that the corresponding bivariate joint probability distribution shows a rich and precise ph

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Nordhausen, Klaus, and Tapio Nummi. "Estimation of the diameter distribution of a stand marked for cutting using finite mixtures." Canadian Journal of Forest Research 37, no. 4 (2007): 817–24. http://dx.doi.org/10.1139/x06-283.

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The aim of this paper is to find a parametric model for the diameter distribution when a sample of trees in a stand is measured by a harvester. It has important applications prior to and during harvesting for the assessment of the production potential of the stand marked for cutting. We apply the finite mixture models for tree species separately. Our data consist of six real forest stands measured in Finland. Our results showed that, for practical implementation, a three-component Lognormal mixture distribution seemed to be a reasonable choice. The subsample analysis indicated that, for certai

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Bremnes, John Bjørnar. "Constrained Quantile Regression Splines for Ensemble Postprocessing." Monthly Weather Review 147, no. 5 (2019): 1769–80. http://dx.doi.org/10.1175/mwr-d-18-0420.1.

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Abstract Statistical postprocessing of ensemble forecasts is widely applied to make reliable probabilistic weather forecasts. Motivated by the fact that nature imposes few restrictions on the shape of forecast distributions, a flexible quantile regression method based on constrained spline functions (CQRS) is proposed and tested on ECMWF Ensemble Prediction System (ENS) wind speed forecasting data at 125 stations in Norway. First, it is demonstrated that constraining quantile functions to be monotone and bounded is preferable. Second, combining an ensemble quantile with the ensemble mean prove

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O. T., John,, Jibasen, D., Abdulkadir, S. S., and Singla, S. "Modelling Service Times Using Some Beta-Based Compound Distribution." African Journal of Mathematics and Statistics Studies 7, no. 4 (2024): 105–21. http://dx.doi.org/10.52589/ajmss-z8zxx03l.

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The design of the queueing model involves modelling the arrival and service processes of the system. Conventionally, the arrival process is assumed to follow Poisson while service times are assumed to be exponentially distributed. Other distributions such as Weibull, uniform, lognormal have been used to model service times however, generalized distributions have not been used in this regard. In recent times, attention have been shifted to generalised families of distributions including Beta generalized family of distributions which led to the development of Beta-based distributions. Distributi

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Wang, Chunwei, Naidan Deng, and Silian Shen. "Numerical Method for a Perturbed Risk Model with Proportional Investment." Mathematics 11, no. 1 (2022): 43. http://dx.doi.org/10.3390/math11010043.

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In this paper, we study the perturbed risk model with a threshold dividend strategy and proportional investment. The insurance companies are allowed to invest their surplus in a financial market consisting of a risk-free asset and a risky asset in fixed proportions; the risky assets are modeled by the jump-diffusion process. Firstly, using the theory of the stochastic process and stochastic analysis, we obtained the integro-differential equations satisfied by the expected discounted dividend payments and the discounted penalty function. Secondly, we obtained the numerical approximate solutions

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