Search results for "Maximum likelihood"
showing 10 items of 53 documents
Searching for localized cosmic particle sources with an unbinned maximum likelihood approach
2006
Abstract An unbinned method to search for localized cosmic particle sources is presented. The expected source shape, the measured background shape, and the estimated angular resolution of individual tracks are used to construct a likelihood function. Estimates of the flux, the position and—in particular—the significance of a source can be readily obtained. A full confidence belt construction to deduce flux limits is presented. General statistical issues when searching for sources of unknown position are discussed.
Precision measurement of the mass of the tau lepton
2014
An energy scan near the $\tau$ pair production threshold has been performed using the BESIII detector. About $24$ pb$^{-1}$ of data, distributed over four scan points, was collected. This analysis is based on $\tau$ pair decays to $ee$, $e\mu$, $eh$, $\mu\mu$, $\mu h$, $hh$, $e\rho$, $\mu\rho$ and $\pi\rho$ final states, where $h$ denotes a charged $\pi$ or $K$. The mass of the $\tau$ lepton is measured from a maximum likelihood fit to the $\tau$ pair production cross section data to be $m_{\tau} = (1776.91\pm0.12 ^{+0.10}_{-0.13}$) MeV/$c^2$, which is currently the most precise value in a single measurement.
The EM imaging reconstruction method in γ-ray astronomy
1998
Abstract The simpler imaging reconstruction methods used for γ-ray coded mask telescopes are based on correlation methods, very fast and simple-to-use but with limitations in the reconstructed image. To improve these results, other reconstruction methods have been developed, such as the maximum entropy methods or the Iterative Removal Of Sources (IROS). However, such kind of methods are slower and can be impracticable for very complex telescopes. In this paper we present an alternative image reconstruction method, based on an iterative maximum likelihood algorithm called the EM algorithm, easy to implement and that can be successfully used for not very complex coded mask systems, as is the …
Modelling of Magnetic Resonance Spectra Using Mixtures for Binned and Truncated Data
2007
Magnetic Resonance Spectroscopy (MRS) provides the biochemical composition of a tissue under study. This information is useful for the in-vivo diagnosis of brain tumours. Prior knowledge of the relative position of the organic compound contributions in the MRS suggests the development of a probabilistic mixture model and its EM-based Maximum Likelihood Estimation for binned and truncated data. Experiments for characterizing and classifying Short Time Echo (STE) spectra from brain tumours are reported.
Measurements of the Branching Fraction andCP-Violation Asymmetries inB0→f0(980)KS0
2005
The authors present measurements of the branching fraction and CP-violating asymmetries in the decay B{sup 0} {yields} f{sub 0}(980)K{sub S}{sup 0}. The results are obtained from a data sample of 123 x 10{sup 6} {Upsilon}(4S) {yields} B{bar B} decays. From a time-dependent maximum likelihood fit they measure the branching fraction {Beta}(B{sup 0} {yields} f{sub 0}(980)({yields}{Pi}{sup +}{pi}{sup 0})K{sup 0}) = (6.0 {+-} 0.9 {+-} 0.6 {+-} 1.2) x 10{sup -6}, the mixing-induced CP violation parameter S = 1.62{sub -0.51}{sup +0.56} {+-} 0.09 {+-} 0.04 and the direct CP violation parameter C = 0.27 {+-} 0.36 {+-} 0.10 {+-} 0.07, where the first errors are statistical, the second systematic and …
Measurement of theCPAsymmetry and Branching Fraction ofB0→ρ0K0
2007
We present a measurement of the branching fraction and time-dependent CP asymmetry of B^0 to rho^0 K^0. The results are obtained from a data sample of 227 10^6 Y4S to BB_ decays collected with the BaBar detector at the PEP2 asymmetric-energy B Factory at SLAC. From a time-dependent maximum likelihood fit yielding 111+/-19 signal events we find B(B^0 to rho^0 K^0)=(4.9+/-0.8+/-0.9) 10^-6, where the first error is statistical and the second systematic. We report the measurement of the CP parameters S=0.20+/-0.52+/-0.24 and C=0.64+/-0.41+/-0.20.
Occlusion-based estimation of independent multinomial random variables using occurrence and sequential information
2017
Abstract This paper deals with the relatively new field of sequence-based estimation in which the goal is to estimate the parameters of a distribution by utilizing both the information in the observations and in their sequence of appearance. Traditionally, the Maximum Likelihood (ML) and Bayesian estimation paradigms work within the model that the data, from which the parameters are to be estimated, is known, and that it is treated as a set rather than as a sequence. The position that we take is that these methods ignore, and thus discard, valuable sequence -based information, and our intention is to obtain ML estimates by “extracting” the information contained in the observations when perc…
Modeling Forest Tree Data Using Sequential Spatial Point Processes
2021
AbstractThe spatial structure of a forest stand is typically modeled by spatial point process models. Motivated by aerial forest inventories and forest dynamics in general, we propose a sequential spatial approach for modeling forest data. Such an approach is better justified than a static point process model in describing the long-term dependence among the spatial location of trees in a forest and the locations of detected trees in aerial forest inventories. Tree size can be used as a surrogate for the unknown tree age when determining the order in which trees have emerged or are observed on an aerial image. Sequential spatial point processes differ from spatial point processes in that the…
A penalized approach for the bivariate ordered logistic model with applications to social and medical data
2018
Bivariate ordered logistic models (BOLMs) are appealing to jointly model the marginal distribution of two ordered responses and their association, given a set of covariates. When the number of categories of the responses increases, the number of global odds ratios to be estimated also increases, and estimation gets problematic. In this work we propose a non-parametric approach for the maximum likelihood (ML) estimation of a BOLM, wherein penalties to the differences between adjacent row and column effects are applied. Our proposal is then compared to the Goodman and Dale models. Some simulation results as well as analyses of two real data sets are presented and discussed.
MLML2R: an R package for maximum likelihood estimation of DNA methylation and hydroxymethylation proportions.
2019
Abstract Accurately measuring epigenetic marks such as 5-methylcytosine (5-mC) and 5-hydroxymethylcytosine (5-hmC) at the single-nucleotide level, requires combining data from DNA processing methods including traditional (BS), oxidative (oxBS) or Tet-Assisted (TAB) bisulfite conversion. We introduce the R package MLML2R, which provides maximum likelihood estimates (MLE) of 5-mC and 5-hmC proportions. While all other available R packages provide 5-mC and 5-hmC MLEs only for the oxBS+BS combination, MLML2R also provides MLE for TAB combinations. For combinations of any two of the methods, we derived the pool-adjacent-violators algorithm (PAVA) exact constrained MLE in analytical form. For the…