[PDF] Top 20 Maximum Likelihood Estimation of Recombination Rates From Population Data
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Maximum Likelihood Estimation of Recombination Rates From Population Data
... move from a specific genealogy with fewer re- This is done by keeping a record of which links were combinations to a specific genealogy with more recom- meaningful in each branch of the old ...occurs from ... See full document
9
Maximum-Likelihood Estimation of Migration Rates and Effective Population Numbers in Two Populations Using a Coalescent Approach
... the estimation of migration rates and effective population sizes is ...a maximum-likelihood framework based on coalescence ...effective population size and the immigration rate ... See full document
12
Approximate maximum likelihood estimation for population genetic inference
... approximate maximum likelihood estimate. Instead of using random samples from the entire parameter space, we adapt stochastic approximation methods and propose two algorithms to approximate the ... See full document
22
Estimation of Population Parameters and Recombination Rates From Single Nucleotide Polymorphisms
... for population growth may be ...arising from preferential selection of loci with alleles of intermediate ...the likelihood function as Pr(X | variability in the first two copies sampled) 5 ... See full document
12
Estimating Recombination Rates From Population Genetic Data
... certain data We compare our new method with the existing impor- sets, accurate estimation of the likelihood surface re- tance sampling method of Griffiths and Marjoram quires much more computation ... See full document
20
Maximum-Likelihood Estimation of Relatedness
... marker data to quantify ...traditional maximum-likelihood estimator in relation to the ...traditional maximum-likelihood estimator exhibits a lower standard error under essentially all ... See full document
16
Maximum likelihood estimation of reviewers' acumen in central review setting: categorical data
... incomplete-data likelihood function and then show the EM algorithm solving proce- ...anesthetist data used by Dawid and Skene and present a new example of a pathology review data from ... See full document
10
Maximum likelihood joint channel and data estimation using genetic algorithms
... A population size of five was suggested in [15] for the ...the population size should be. An appropriate population size also depends on the application ...the population size n p is given by ... See full document
5
Maximum Likelihood Estimation of Population Growth Rates Based on the Coalescent
... a population where Q is constant, and in Both analytic and simulation results show that the principle this should be ...the population has been growing the most rootward finite number of individuals are ... See full document
6
Maximum-Likelihood Estimation of Rates of Recombination Within Mating-Type Regions
... include recombination suppression over large genomic tracts and cosegregation of genes of various functions, not necessarily related to ...a maximum-likelihood estimate of the rate of ... See full document
14
Joint Maximum Likelihood Channel Estimation and Data Detection for MIMO Systems
... the data length N = 50 was very small and each OHRSA- ML evaluation was performed very ...also from Fig. 3 which shows the bit error rates (BERs) calculated by the ML detectors using the estimated ... See full document
5
Maximum-Likelihood Estimation of Admixture Proportions From Genetic Data
... inferred from samples quently occur when different populations, having been taken from current parental and admixed populations, isolated and differentiated over a period of time, over- the ... See full document
20
Unit Root Tests in Panel Data: Weighted Symmetric Estimation and Maximum Likelihood Estimation
... generated from the RANNOR function in ...generated from N (0, 1) independently of e it ...the maximum likelihood algorithm for model ...ml,ran from PROC ... See full document
103
Estimation of the Reliability Measures of a Three component System with Human Errors and Common Cause Failures
... Therefore, the M L estimators are generally hard to beat consistently, even in small samples and our simulation results showed a strong preference for the M L estimation method for situations arising in practical ... See full document
7
Blind Joint Maximum Likelihood Channel Estimation and Data Detection for SIMO Systems
... channel estimation and data ...received data samples to achieve a near optimal so- lution of the maximum likelihood sequence estimation for data ... See full document
5
A simple approach to maximum intractable likelihood estimation
... the likelihood is intractable, such a statistic may not be ...the likelihood approx- imation in this setting, it is difficult to draw useful conclusions from such a char- ...the data and hence ... See full document
24
Maximum Likelihood Estimation of Feature Based Distributions
... Second, models can be defined where multiple features are permitted to interact. For example, suppose features F and G from Table 1 are em- bedded in a larger feature system. The machine in Figure 5 can be defined ... See full document
10
On the Approximate Maximum Likelihood Estimation for Diffusion Processes
... The paper is organized as follows. In Section 2, we outline the transition density approxima- tions of A¨ıt-Sahalia (1999, 2002). Some preliminary analysis needed for studying the AMLE is presented in Section 3. Section ... See full document
39
Smooth nonparametric maximum likelihood estimation for population pharmacokinetics, with application to quinidine
... Because the SNP method is based on the· principle of maximum likelihood and because the SNP density has a convenient representation, subsequent computations essential to a complete stati[r] ... See full document
33
Asymptotics of Maximum Composite Likelihood Estimation for Geostatistical Data
... Stein et al. (2004) extended the above work by investigating the effect of conditioning on observations that are not necessarily the nearest neighbours. This is done in the context of restricted maximum com- ... See full document
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