scholarly journals Maximum-Likelihood Estimation of Migration Rates and Effective Population Numbers in Two Populations Using a Coalescent Approach

Genetics ◽  
1999 ◽  
Vol 152 (2) ◽  
pp. 763-773 ◽  
Author(s):  
Peter Beerli ◽  
Joseph Felsenstein
Keyword(s):  
Maximum Likelihood ◽  
Mutation Rate ◽  
Likelihood Estimation ◽  
Effective Population ◽  
Migration Rates ◽  
Coalescent Approach ◽  
Population Sizes ◽  
Two Populations ◽  
Better Than ◽  
Population Numbers

Abstract A new method for the estimation of migration rates and effective population sizes is described. It uses a maximum-likelihood framework based on coalescence theory. The parameters are estimated by Metropolis-Hastings importance sampling. In a two-population model this method estimates four parameters: the effective population size and the immigration rate for each population relative to the mutation rate. Summarizing over loci can be done by assuming either that the mutation rate is the same for all loci or that the mutation rates are gamma distributed among loci but the same for all sites of a locus. The estimates are as good as or better than those from an optimized FST-based measure. The program is available on the World Wide Web at http://evolution.genetics.washington.edu/lamarc.html/.

An Additive NHPP-Based Reliability Model of Wireless Sensor Networks

2014 ◽  
Vol 602-605 ◽  
pp. 3206-3212
Author(s):  
Bo Zhao ◽  
Jian Feng Yang ◽  
Ming Zhao ◽  
Qi Li ◽  
Yan Liu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Maximum Likelihood ◽  
Likelihood Estimation ◽  
Wireless Sensor ◽  
Reliability Model ◽  
Unknown Parameters ◽  
Failure Data ◽  
Better Than

As the Wireless Sensor Networks (WSNs) are widely implemented in various fields recent years, the quality of WSNs has been increasingly concerned. WSNs can usually be divided into sub-nets, which assumed to work or fail independently. Through the failure data of those sub-nets, the additive NHPP model for reliability evaluation is composed, and then the maximum likelihood estimation is applied to estimate the unknown parameters in the model. Finally, the simulation shows that the additive NHPP model is better than general NHPP model under certain circumstances.

scholarly journals Falciparum malaria from coastal Tanzania and Zanzibar remains highly connected despite effective control efforts on the archipelago

2019 ◽  
Author(s):  
Andrew Morgan ◽  
Nicholas Brazeau ◽  
Billy Ngasala ◽  
Lwidiko Mhamilawa ◽  
Madeline Denton ◽  
...  
Keyword(s):  
Malaria Incidence ◽  
Effective Control ◽  
Effective Population ◽  
Limited Sampling ◽  
Shared Ancestry ◽  
Population Sizes ◽  
The Impact ◽  
Two Populations ◽  
Large Sections ◽  
Population Genetic Analyses

Abstract Background: Tanzania’s Zanzibar archipelago has made significant gains in malaria control over the last decade and is a target for malaria elimination. Despite consistent implementation of effective tools since 2002, elimination has not been achieved. Importation of parasites from outside of the archipelago is thought to be an important cause of malaria’s persistence, but this paradigm has not been studied using modern genetic tools.Methods: We used whole-genome sequencing (WGS) to investigate the impact of importation, employing population genetic analyses of Plasmodium falciparum isolates from both the archipelago and mainland Tanzania. We assessed ancestry, levels of genetic diversity and differentiation, patterns of relatedness, and patterns of selection between these two populations by leveraging recent advances in deconvolution of genomes from polyclonal malaria infections.Results: We identified significant decreases in the effective population sizes in both populations in the timeframe of decreasing malaria transmission in Tanzania. Identity by descent analysis showed that parasites in the two populations shared large sections of their genomes, on the order of 5 cM, suggesting shared ancestry within the last 10 generations. Even with limited sampling,, we demonstrate a pair of isolates between the mainland and Zanzibar that are related at the expected level of half-siblings, consistent with recent importation.Conclusions: These findings suggest that importation plays an increasing role for malaria incidence on Zanzibar and demonstrate the value of genomic approaches for identifying corridors of parasite movement to the island.

scholarly journals Falciparum malaria from coastal Tanzania and Zanzibar remains highly connected despite effective control efforts on the archipelago

2020 ◽  
Author(s):  
Andrew Morgan ◽  
Nicholas Brazeau ◽  
Billy Ngasala ◽  
Lwidiko Mhamilawa ◽  
Madeline Denton ◽  
...  
Keyword(s):  
Malaria Incidence ◽  
Effective Control ◽  
Effective Population ◽  
Identity By Descent ◽  
Limited Sampling ◽  
Shared Ancestry ◽  
Population Sizes ◽  
The Impact ◽  
Two Populations ◽  
Population Genetic Analyses

Abstract Background Tanzania’s Zanzibar archipelago has made significant gains in malaria control over the last decade and is a target for malaria elimination. Despite consistent implementation of effective tools since 2002, elimination has not been achieved. Importation of parasites from outside of the archipelago is thought to be an important cause of malaria’s persistence, but this paradigm has not been studied using modern genetic tools. Methods Whole-genome sequencing (WGS) was used to investigate the impact of importation, employing population genetic analyses of Plasmodium falciparum isolates from both the archipelago and mainland Tanzania. Ancestry, levels of genetic diversity and differentiation, patterns of relatedness, and patterns of selection between these two populations were assessed by leveraging recent advances in deconvolution of genomes from polyclonal malaria infections. Results Significant decreases in the effective population sizes were inferred in both populations that coincide with a period of decreasing malaria transmission in Tanzania. Identity by descent analysis showed that parasites in the two populations shared long segments of their genomes, on the order of 5 cM, suggesting shared ancestry within the last 10 generations. Even with limited sampling, two of isolates between the mainland and Zanzibar were identified that are related at the expected level of half-siblings, consistent with recent importation. Conclusions These findings suggest that importation plays an important role for malaria incidence on Zanzibar and demonstrate the value of genomic approaches for identifying corridors of parasite movement to the island.

scholarly journals A New Generalized t Distribution Based on a Distribution Construction Method

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2413
Author(s):  
Ruijie Guan ◽  
Xu Zhao ◽  
Weihu Cheng ◽  
Yaohua Rong
Keyword(s):  
Maximum Likelihood ◽  
Em Algorithm ◽  
Iterative Algorithm ◽  
Likelihood Estimation ◽  
Estimation Methods ◽  
Modified Method ◽  
The Em Algorithm ◽  
Likelihood Approach ◽  
T Distribution ◽  
Better Than

In this paper, a new generalized t (new Gt) distribution based on a distribution construction approach is proposed and proved to be suitable for fitting both the data with high kurtosis and heavy tail. The main innovation of this article consists of four parts. First of all, the main characteristics and properties of this new distribution are outined. Secondly, we derive the explicit expression for the moments of order statistics as well as its corresponding variance–covariance matrix. Thirdly, we focus on the parameter estimation of this new Gt distribution and introduce several estimation methods, such as a modified method of moments (MMOM), a maximum likelihood estimation (MLE) using the EM algorithm, a novel iterative algorithm to acquire MLE, and improved probability weighted moments (IPWM). Through simulation studies, it can be concluded that the IPWM estimation performs better than the MLE using the EM algorithm and the MMOM in general. The newly-proposed iterative algorithm has better performance than the EM algorithm when the sample kurtosis is greater than 2.7. For four parameters of the new Gt distribution, a profile maximum likelihood approach using the EM algorithm is developed to deal with the estimation problem and obtain acceptable.

scholarly journals Stochastic Interplay between Mutation and Recombination during the Acquisition of Drug Resistance Mutations in Human Immunodeficiency Virus Type 1

2005 ◽  
Vol 79 (21) ◽  
pp. 13572-13578 ◽  
Author(s):  
Christian L. Althaus ◽  
Sebastian Bonhoeffer
Keyword(s):  
Human Immunodeficiency Virus ◽  
Drug Resistance ◽  
Population Size ◽  
Mutation Rate ◽  
Population Genetic ◽  
Resistance Mutations ◽  
Effective Population ◽  
Drug Resistance Mutations ◽  
Immunodeficiency Virus ◽  
Population Sizes

ABSTRACT The emergence of drug resistance mutations in human immunodeficiency virus (HIV) has been a major setback in the treatment of infected patients. Besides the high mutation rate, recombination has been conjectured to have an important impact on the emergence of drug resistance. Population genetic theory suggests that in populations limited in size recombination may facilitate the acquisition of beneficial mutations. The viral population in an infected patient may indeed represent such a population limited in size, since current estimates of the effective population size range from 500 to 105. To address the effects of limited population size, we therefore expand a previously described deterministic population genetic model of HIV replication by incorporating the stochastic processes that occur in finite populations of infected cells. Using parameter estimates from the literature, we simulate the evolution of drug-resistant viral strains. The simulations show that recombination has only a minor effect on the rate of acquisition of drug resistance mutations in populations with effective population sizes as small as 1,000, since in these populations, viral strains typically fix beneficial mutations sequentially. However, for intermediate effective population sizes (104 to 105), recombination can accelerate the evolution of drug resistance by up to 25%. Furthermore, a reduction in population size caused by drug therapy can be overcome by a higher viral mutation rate, leading to a faster evolution of drug resistance.

Maximum Likelihood Estimation of Population Growth Rates Based on the Coalescent

Genetics ◽  
1998 ◽  
Vol 149 (1) ◽  
pp. 429-434 ◽  
Author(s):  
Mary K Kuhner ◽  
Jon Yamato ◽  
Joseph Felsenstein
Keyword(s):  
Growth Rate ◽  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Population Growth ◽  
Growth Rates ◽  
Population Growth Rate ◽  
Likelihood Estimation ◽  
Effective Population ◽  
Population Growth Rates ◽  
Neutral Mutation Rate

Abstract We describe a method for co-estimating 4Neμ (four times the product of effective population size and neutral mutation rate) and population growth rate from sequence samples using Metropolis-Hastings sampling. Population growth (or decline) is assumed to be exponential. The estimates of growth rate are biased upwards, especially when 4Neμ is low; there is also a slight upwards bias in the estimate of 4Neμ itself due to correlation between the parameters. This bias cannot be attributed solely to Metropolis-Hastings sampling but appears to be an inherent property of the estimator and is expected to appear in any approach which estimates growth rate from genealogy structure. Sampling additional unlinked loci is much more effective in reducing the bias than increasing the number or length of sequences from the same locus.

scholarly journals Bayesian phylodynamics of avian influenza virus H9N2 in Asia with time-dependent predictors of migration

2018 ◽  
Author(s):  
Jing Yang ◽  
Nicola F. Müller ◽  
Remco Bouckaert ◽  
Bing Xu ◽  
Alexei J. Drummond
Keyword(s):  
Time Series ◽  
Avian Influenza ◽  
Wild Bird ◽  
Time Dependent ◽  
Poultry Production ◽  
Geographic Proximity ◽  
Effective Population ◽  
Migration Rates ◽  
Bird Populations ◽  
Population Sizes

AbstractModel-based phylodynamic approaches recently employed generalized linear models (GLMs) to uncover potential predictors of viral spread. Very recently some of these models have allowed both the predictors and their coefficients to be time-dependent. However, these studies mainly focused on predictors that are assumed to be constant through time. Here we inferred the phylodynamics of H9N2 viruses isolated in 12 Asian countries and regions under both discrete trait analysis (DTA) and structured coalescent (MASCOT) approaches. Using MASCOT we applied a new time-dependent GLM to uncover the underlying factors behind H9N2 spread. We curated a rich set of time-series predictors including annual international live poultry trade and national poultry production figures. This time-dependent phylodynamic prediction model was compared to commonly employed time-independent alternatives. Additionally the time-dependent MASCOT model allowed for the estimation of viral effective sub-population sizes and their changes through time and these effective population dynamics within each country were predicted by a GLM. International annual poultry trade is a strongly supported predictor of virus migration rates. There was also strong support for geographic proximity as a predictor of migration rate in all GLMs investigated. In time-dependent MASCOT models, national poultry production was also identified as a predictor of virus genetic diversity through time and this signal was obvious in mainland China and Bangladesh. Our application of a recently introduced time-dependent GLM predictors integrated rich time-series data in Bayesian phylodynamic prediction. We demonstrated the contribution of poultry trade and geographic proximity (potentially unheralded wild bird movements) to avian influenza spread in Asia. To gain a better understanding of the drivers of H9N2 spread, we suggest increased surveillance of the H9N2 virus in countries that are currently under-sampled as well as in wild bird populations in the most affected countries.Author summaryWhat drives the geographic dispersal and genetic diversity of H9N2 avian influenza virus in Asia? We used two model-based approaches, DTA and MASCOT, to reconstruct the phylogeographic dynamics of the virus. Further, multiple potential predictors were used to inform the virus spread and population dynamics by GLMs. Here, we maximised the power of time-series predictors in Bayesian phylodynamic prediction. For the first time, we were able to quantify the contribution of both time-series and constant predictors to both migration rates and effective population sizes in a structured population. We identified a positive association of international poultry trade and national poultry production time-series with virus migration rates and effective population sizes respectively. We also identify geographic proximity as a strongly supported driver to virus migration rates and this points to the potential role of wild bird populations in virus dispersal across countries. Our study is a practical exemplar of the use of temporal information in predictors to model heterogeneous spatial diffusion and population dynamic processes and provides direction to H9N2 control efforts in Asia.

scholarly journals Odd Lindley-Lomax Model: Statistical Properties and Applications

1970 ◽  
pp. 419-430
Author(s):  
M. Masoom Ali ◽  
Mustafa Ç. Korkmaz ◽  
Haitham M. Yousof ◽  
Nadeem Shafique Butt
Keyword(s):  
Maximum Likelihood ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
Good Alternative ◽  
Model Parameters ◽  
Lifetime Data ◽  
Monte Carlo Simulation Study ◽  
Computational Aspects ◽  
Maximum Likelihood Estimation Method ◽  
Better Than

 In this work, we focus on some new theoretical and computational aspects of the Odd Lindley-Lomax model. The maximum likelihood estimation method is used to estimate the model parameters. We show empirically the importance and flexibility of the new model in modeling two types of aircraft windshield lifetime data. This model is much better than exponentiated Lomax, gamma Lomax, beta Lomax and Lomax models so the Odd Lindley-Lomax lifetime model is a good alternative to these models in modeling aircraft windshield data. A Monte Carlo simulation study is used to assess the performance of the maximum likelihood estimators. 

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