967 resultados para Intractable Likelihood
Resumo:
Muscoidea is a significant dipteran clade that includes house flies (Family Muscidae), latrine flies (F. Fannidae), dung flies (F. Scathophagidae) and root maggot flies (F. Anthomyiidae). It is comprised of approximately 7000 described species. The monophyly of the Muscoidea and the precise relationships of muscoids to the closest superfamily the Oestroidea (blow flies, flesh flies etc) are both unresolved. Until now mitochondrial (mt) genomes were available for only two of the four muscoid families precluding a thorough test of phylogenetic relationships using this data source. Here we present the first two mt genomes for the families Fanniidae (Euryomma sp.) (family Fanniidae) and Anthomyiidae (Delia platura (Meigen, 1826)). We also conducted phylogenetic analyses containing of these newly sequenced mt genomes plus 15 other species representative of dipteran diversity to address the internal relationship of Muscoidea and its systematic position. Both maximum-likelihood and Bayesian analyses suggested that Muscoidea was not a monophyletic group with the relationship: (Fanniidae + Muscidae) + ((Anthomyiidae + Scathophagidae) + (Calliphoridae + Sarcophagidae)), supported by the majority of analysed datasets. This also infers that Oestroidea was paraphyletic in the majority of analyses. Divergence time estimation suggested that the earliest split within the Calyptratae, separating (Tachinidae + Oestridae) from the remaining families, occurred in the Early Eocene. The main divergence within the paraphyletic muscoidea grade was between Fanniidae + Muscidae and the lineage ((Anthomyiidae + Scathophagidae) + (Calliphoridae + Sarcophagidae)) which occurred in the Late Eocene
Resumo:
This thesis studies quantile residuals and uses different methodologies to develop test statistics that are applicable in evaluating linear and nonlinear time series models based on continuous distributions. Models based on mixtures of distributions are of special interest because it turns out that for those models traditional residuals, often referred to as Pearson's residuals, are not appropriate. As such models have become more and more popular in practice, especially with financial time series data there is a need for reliable diagnostic tools that can be used to evaluate them. The aim of the thesis is to show how such diagnostic tools can be obtained and used in model evaluation. The quantile residuals considered here are defined in such a way that, when the model is correctly specified and its parameters are consistently estimated, they are approximately independent with standard normal distribution. All the tests derived in the thesis are pure significance type tests and are theoretically sound in that they properly take the uncertainty caused by parameter estimation into account. -- In Chapter 2 a general framework based on the likelihood function and smooth functions of univariate quantile residuals is derived that can be used to obtain misspecification tests for various purposes. Three easy-to-use tests aimed at detecting non-normality, autocorrelation, and conditional heteroscedasticity in quantile residuals are formulated. It also turns out that these tests can be interpreted as Lagrange Multiplier or score tests so that they are asymptotically optimal against local alternatives. Chapter 3 extends the concept of quantile residuals to multivariate models. The framework of Chapter 2 is generalized and tests aimed at detecting non-normality, serial correlation, and conditional heteroscedasticity in multivariate quantile residuals are derived based on it. Score test interpretations are obtained for the serial correlation and conditional heteroscedasticity tests and in a rather restricted special case for the normality test. In Chapter 4 the tests are constructed using the empirical distribution function of quantile residuals. So-called Khmaladze s martingale transformation is applied in order to eliminate the uncertainty caused by parameter estimation. Various test statistics are considered so that critical bounds for histogram type plots as well as Quantile-Quantile and Probability-Probability type plots of quantile residuals are obtained. Chapters 2, 3, and 4 contain simulations and empirical examples which illustrate the finite sample size and power properties of the derived tests and also how the tests and related graphical tools based on residuals are applied in practice.
Resumo:
The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.
Resumo:
A set of sufficient conditions to construct lambda-real symbol Maximum Likelihood (ML) decodable STBCs have recently been provided by Karmakar et al. STBCs satisfying these sufficient conditions were named as Clifford Unitary Weight (CUW) codes. In this paper, the maximal rate (as measured in complex symbols per channel use) of CUW codes for lambda = 2(a), a is an element of N is obtained using tools from representation theory. Two algebraic constructions of codes achieving this maximal rate are also provided. One of the constructions is obtained using linear representation of finite groups whereas the other construction is based on the concept of right module algebra over non-commutative rings. To the knowledge of the authors, this is the first paper in which matrices over non-commutative rings is used to construct STBCs. An algebraic explanation is provided for the 'ABBA' construction first proposed by Tirkkonen et al and the tensor product construction proposed by Karmakar et al. Furthermore, it is established that the 4 transmit antenna STBC originally proposed by Tirkkonen et al based on the ABBA construction is actually a single complex symbol ML decodable code if the design variables are permuted and signal sets of appropriate dimensions are chosen.
Resumo:
We present a search for associated production of the standard model (SM) Higgs boson and a $Z$ boson where the $Z$ boson decays to two leptons and the Higgs decays to a pair of $b$ quarks in $p\bar{p}$ collisions at the Fermilab Tevatron. We use event probabilities based on SM matrix elements to construct a likelihood function of the Higgs content of the data sample. In a CDF data sample corresponding to an integrated luminosity of 2.7 fb$^{-1}$ we see no evidence of a Higgs boson with a mass between 100 GeV$/c^2$ and 150 GeV$/c^2$. We set 95% confidence level (C.L.) upper limits on the cross-section for $ZH$ production as a function of the Higgs boson mass $m_H$; the limit is 8.2 times the SM prediction at $m_H = 115$ GeV$/c^2$.
Resumo:
We report a measurement of the single top quark production cross section in 2.2 ~fb-1 of p-pbar collision data collected by the Collider Detector at Fermilab at sqrt{s}=1.96 TeV. Candidate events are classified as signal-like by three parallel analyses which use likelihood, matrix element, and neural network discriminants. These results are combined in order to improve the sensitivity. We observe a signal consistent with the standard model prediction, but inconsistent with the background-only model by 3.7 standard deviations with a median expected sensitivity of 4.9 standard deviations. We measure a cross section of 2.2 +0.7 -0.6(stat+sys) pb, extract the CKM matrix element value |V_{tb}|=0.88 +0.13 -0.12 (stat+sys) +- 0.07(theory), and set the limit |V_{tb}|>0.66 at the 95% C.L.
Resumo:
We present a measurement of the top quark mass and of the top-antitop pair production cross section using p-pbar data collected with the CDFII detector at the Tevatron Collider at the Fermi National Accelerator Laboratory and corresponding to an integrated luminosity of 2.9 fb-1. We select events with six or more jets satisfying a number of kinematical requirements imposed by means of a neural network algorithm. At least one of these jets must originate from a b quark, as identified by the reconstruction of a secondary vertex inside the jet. The mass measurement is based on a likelihood fit incorporating reconstructed mass distributions representative of signal and background, where the absolute jet energy scale (JES) is measured simultaneously with the top quark mass. The measurement yields a value of 174.8 +- 2.4(stat+JES) ^{+1.2}_{-1.0}(syst) GeV/c^2, where the uncertainty from the absolute jet energy scale is evaluated together with the statistical uncertainty. The procedure measures also the amount of signal from which we derive a cross section, sigma_{ttbar} = 7.2 +- 0.5(stat) +- 1.0 (syst) +- 0.4 (lum) pb, for the measured values of top quark mass and JES.
Resumo:
We report the observation of electroweak single top quark production in 3.2 fb-1 of pp̅ collision data collected by the Collider Detector at Fermilab at √s=1.96 TeV. Candidate events in the W+jets topology with a leptonically decaying W boson are classified as signal-like by four parallel analyses based on likelihood functions, matrix elements, neural networks, and boosted decision trees. These results are combined using a super discriminant analysis based on genetically evolved neural networks in order to improve the sensitivity. This combined result is further combined with that of a search for a single top quark signal in an orthogonal sample of events with missing transverse energy plus jets and no charged lepton. We observe a signal consistent with the standard model prediction but inconsistent with the background-only model by 5.0 standard deviations, with a median expected sensitivity in excess of 5.9 standard deviations. We measure a production cross section of 2.3-0.5+0.6(stat+sys) pb, extract the value of the Cabibbo-Kobayashi-Maskawa matrix element |Vtb|=0.91-0.11+0.11(stat+sys)±0.07 (theory), and set a lower limit |Vtb|>0.71 at the 95% C.L., assuming mt=175 GeV/c2.
Resumo:
We report the observation of electroweak single top quark production in 3.2 fb-1 of ppbar collision data collected by the Collider Detector at Fermilab at sqrt{s}=1.96 TeV. Candidate events in the W+jets topology with a leptonically decaying W boson are classified as signal-like by four parallel analyses based on likelihood functions, matrix elements, neural networks, and boosted decision trees. These results are combined using a super discriminant analysis based on genetically evolved neural networks in order to improve the sensitivity. This combined result is further combined with that of a search for a single top quark signal in an orthogonal sample of events with missing transverse energy plus jets and no charged lepton. We observe a signal consistent with the standard model prediction but inconsistent with the background-only model by 5.0 standard deviations, with a median expected sensitivity in excess of 5.9 standard deviations. We measure a production cross section of 2.3+0.6-0.5(stat+sys) pb, extract the CKM matrix element value |Vtb|=0.91+0.11-0.11 (stat+sys)+-0.07(theory), and set a lower limit |Vtb|>0.71 at the 95% confidence level, assuming m_t=175 GeVc^2.
Resumo:
Tutkimuksen tarkoituksena oli selvittää Opaskoirakoulun pentutestissä mitattavien ominaisuuksien perinnölliset tunnusluvut sekä niihin vaikuttavat tekijät. Aineisto koostui Opaskoirakoululla vuosina 1988–2008 pentutestin suorittaneista koirista (900 kpl). Suomen Kennelliito ry:stä saatiin sukulaisuusaineisto, johon täydennettiin rekisteriin kuulumattomat koirat. Tutkittavia ominaisuuksia oli 11 kappaletta: käyttäytyminen sylissä, luoksetulo, kontakti, taistelu, alistus, palautuminen, ääniherkkyys, käyttäytyminen pöydällä, seuraaminen, toimintakyky ja hermorakenne. Kaikki ominaisuudet arvostellaan pentutestissä valmiiden käyttäytymismallien mukaisesti. Aineiston esikäsittelyyn ja alustaviin analyyseihin käytettiin Microsoft Office Excel 2003-ohjelmaa sekä WSYS-L ja XWSYS-ohjelmistoja. Kiinteiden tekijöiden luokitteluun ja merkitsevyyden testaamiseen käytettiin WSYS-L ja XWSYS-ohjelmistoa. Varianssikomponentit sekä periytymisasteet laskettiin Restricted Maximum Likelihood (REML)-menetelmällä käyttäen VCE6-ohjelmistoa Tutkittujen ominaisuuksien periytymisasteiden arviot olivat alhaisia tai keskinkertaisia (h2= 0,07-0,39). Korkeimmat periytymisasteiden arviot olivat ominaisuuksilla alistus (0,39), toimintakyky (0,32) ja kontakti (0,31). Ominaisuuksien väliset geneettiset korrelaatiot olivat pääosin positiivisia. Poikkeuksen muodosti ominaisuus alistus, joka oli negatiivisesti korreloitunut palautumisen (-0,47) ja seuraamisen (-0,64) kanssa. Osa ominaisuuksista oli erittäin voimakkaasti korreloituneita (r > 0,8). Fenotyyppiset korrelaatiot vaihtelivat välillä 0,11–0,73 ja olivat geneettisiä korrelaatioita matalampia. Tämän tutkimuksen perusteella ominaisuuksissa käyttäytyminen sylissä, luoksetulo, kontakti, taistelu, alistus, ääniherkkyys, käyttäytyminen pöydällä ja toimintakyky on geneettistä vaihtelua ja sen perusteella niitä on mahdollista muuttaa haluttuun suuntaan jalostuksen avulla.
Resumo:
Leaf and needle biomasses are key factors in forest health. Insects that feed on needles cause growth losses and tree mortality. Insect outbreaks in Finnish forests have increased rapidly during the last decade and due to climate change the damages are expected to become more serious. There is a need for cost-efficient methods for inventorying these outbreaks. Remote sensing is a promising means for estimating forests and damages. The purpose of this study is to investigate the usability of airborne laser scanning in estimating Scots pine defoliation caused by the common pine sawfly (Diprion pini L.). The study area is situated in Ilomantsi district, eastern Finland. Study materials included high-pulse airborne laser scannings from July and October 2008. Reference data consisted of 90 circular field plots measured in May-June 2009. Defoliation percentage on these field plots was estimated visually. The study was made on plot-level and methods used were linear regression, unsupervised classification, Maximum likelihood method, and stepwise linear regression. Field plots were divided in defoliation classes in two different ways: When divided in two classes the defoliation percentages used were 0–20 % and 20–100 % and when divided in four classes 0–10 %, 10–20 %, 20–30 % and 30–100 %. The results varied depending on method and laser scanning. In the first laser scanning the best results were obtained with stepwise linear regression. The kappa value was 0,47 when using two classes and 0,37 when divided in four classes. In the second laser scanning the best results were obtained with Maximum likelihood. The kappa values were 0,42 and 0,37, correspondingly. The feature that explained defoliation best was vegetation index (pulses reflected from height > 2m / all pulses). There was no significant difference in the results between the two laser scannings so the seasonal change in defoliation could not be detected in this study.
Resumo:
We report a measurement of the single top quark production cross section in 2.2 ~fb-1 of p-pbar collision data collected by the Collider Detector at Fermilab at sqrt{s}=1.96 TeV. Candidate events are classified as signal-like by three parallel analyses which use likelihood, matrix element, and neural network discriminants. These results are combined in order to improve the sensitivity. We observe a signal consistent with the standard model prediction, but inconsistent with the background-only model by 3.7 standard deviations with a median expected sensitivity of 4.9 standard deviations. We measure a cross section of 2.2 +0.7 -0.6(stat+sys) pb, extract the CKM matrix element value |V_{tb}|=0.88 +0.13 -0.12 (stat+sys) +- 0.07(theory), and set the limit |V_{tb}|>0.66 at the 95% C.L.
Resumo:
A precision measurement of the top quark mass m_t is obtained using a sample of ttbar events from ppbar collisions at the Fermilab Tevatron with the CDF II detector. Selected events require an electron or muon, large missing transverse energy, and exactly four high-energy jets, at least one of which is tagged as coming from a b quark. A likelihood is calculated using a matrix element method with quasi-Monte Carlo integration taking into account finite detector resolution and jet mass effects. The event likelihood is a function of m_t and a parameter DJES to calibrate the jet energy scale /in situ/. Using a total of 1087 events, a value of m_t = 173.0 +/- 1.2 GeV/c^2 is measured.
Resumo:
We report a measurement of the top quark mass, m_t, obtained from ppbar collisions at sqrt(s) = 1.96 TeV at the Fermilab Tevatron using the CDF II detector. We analyze a sample corresponding to an integrated luminosity of 1.9 fb^-1. We select events with an electron or muon, large missing transverse energy, and exactly four high-energy jets in the central region of the detector, at least one of which is tagged as coming from a b quark. We calculate a signal likelihood using a matrix element integration method, with effective propagators to take into account assumptions on event kinematics. Our event likelihood is a function of m_t and a parameter JES that determines /in situ/ the calibration of the jet energies. We use a neural network discriminant to distinguish signal from background events. We also apply a cut on the peak value of each event likelihood curve to reduce the contribution of background and badly reconstructed events. Using the 318 events that pass all selection criteria, we find m_t = 172.7 +/- 1.8 (stat. + JES) +/- 1.2 (syst.) GeV/c^2.
Resumo:
This paper reports a measurement of the cross section for the pair production of top quarks in ppbar collisions at sqrt(s) = 1.96 TeV at the Fermilab Tevatron. The data was collected from the CDF II detector in a set of runs with a total integrated luminosity of 1.1 fb^{-1}. The cross section is measured in the dilepton channel, the subset of ttbar events in which both top quarks decay through t -> Wb -> l nu b where l = e, mu, or tau. The lepton pair is reconstructed as one identified electron or muon and one isolated track. The use of an isolated track to identify the second lepton increases the ttbar acceptance, particularly for the case in which one W decays as W -> tau nu. The purity of the sample may be further improved at the cost of a reduction in the number of signal events, by requiring an identified b-jet. We present the results of measurements performed with and without the request of an identified b-jet. The former is the first published CDF result for which a b-jet requirement is added to the dilepton selection. In the CDF data there are 129 pretag lepton + track candidate events, of which 69 are tagged. With the tagging information, the sample is divided into tagged and untagged sub-samples, and a combined cross section is calculated by maximizing a likelihood. The result is sigma_{ttbar} = 9.6 +/- 1.2 (stat.) -0.5 +0.6 (sys.) +/- 0.6 (lum.) pb, assuming a branching ratio of BR(W -> ell nu) = 10.8% and a top mass of m_t = 175 GeV/c^2.