Log-likelihood ratio

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Topic: Log-likelihood ratio

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	BCB at ISU- Speaker Information
		The expected value of the log likelihood calculated using the first approach had a poor relationship with power, but the expected value of the log likelihood ratio calculated using the second approach had a strong correlation with the mean of the log likelihood ratio.
		Because the mean of the log likelihood ratio did not have a strong correlation with the power, this mean may not be a good indicator of the power of a design.
		The test statistic most commonly used for detection of QTL is the log likelihood ratio.
	www.bcb.iastate.edu /seminars/02-08-02.html (435 words)

	meme-explanation.html
		The statistical significance of a motif is based on its log likelihood ratio, its width and number of occurrences, the background letter frequencies (given in the command line summary), and the size of the training set.
		(In random sequences each position is independent with letters chosen according to the background letter frequencies.) The log likelihood ratio is the logarithm of the ratio of the probability of the occurrences of the motif given the motif model (likelihood given the motif) versus their probability given the background model (likelihood given the null model).
		The E-value is an estimate of the expected number of motifs with the given log likelihood ratio (or higher), and with the same width and number of occurrences, that one would find in a similarly sized set of random sequences.
	meme.sdsc.edu /meme/website/meme-explanation.html (1732 words)

	Likelihood-ratio test - Wikipedia, the free encyclopedia
		Many common test statistics such as the Z-test, the F-test, Pearson's chi-square test and the G-test can be phrased as log-likelihood ratios or approximations thereof.
		For the general contingency table, we can write the log-likelihood ratio statistic as
		If that ratio is Λ and the null hypothesis holds, then for commonly occurring families of probability distributions, −2 log Λ has a particularly handy asymptotic distribution.
	www.wikipedia.org /wiki/Likelihood_ratio (654 words)

	Stats: Likelihood ratio slide rule
		The likelihood ratio slide rule that I developed was inspired by the Fagan nomogram which also uses logarithms.
		For example, H pylori is found in 48% of dyspeptic patients in the community (the pre-test probability), so therefore a positive rapid blood test with a likelihood ratio of 9.8 applied to this population would give a post-test probability (or predictive value) of 90% (this can be estimated using a simple calculation or a nomogram).
		The likelihood ratio slide rule allows you to compute the post-test probability of a disease given the pre-test probability and the likelihood ratio of a diagnostic test.
	www.cmh.edu /stats/sliderule.asp (1290 words)

	ERP 9:1 Comparison of Likelihood Ratio and Pearsonian Rasch Fit
		The likelihood ratio test is based on the ratio of the likelihood of the response pattern based on a single overall ability estimate and the likelihood of the response pattern based on the J estimated subset abilities.
		To examine the similarity between the transformed likelihood ratio chi-square and the unweighted between fit statistic, the values for both statistics were correlated for the 1,800 cases simulated to fit the model.
		This is a conditional likelihood ratio test which is based on the conditional estimates of the item parameters and does not require the estimation of person abilities.
	www.rasch.org /erp4.htm (4071 words)

	lecture_october_18.doc
		Log Likelihood ratio test Suppose you were to set (=0 (null hypothesis) and that you calculated the log-likelihood of your sample constraining (to be 0.
		The likelihood ratio test requires that we re-estimate the model setting (=0 (that is with no covariates in our case): > stcox, estimate Cox regression -- Breslow method for ties No.
		If it turns out that the true (is 0, it follows that the log likelihood of the constrained model should be close or identical to the log likelihood of the unconstrained model.
	www.ssc.wisc.edu /~palloni/952_04/lectures/lecture_october_18.doc (713 words)

	Statistical Reliability: Class No. 13
		You need to understand the logic behind the likelihood ratio method to be able to use this method correctly.
		The likelihood ratio test plays the role of the F test in many area of application where normality cannot be assumed
		The likelihood ratio method will open a whole new world of statistical application outside the traditional linear model and normal distribution framework.
	web.utk.edu /~leon/rel/class/class97/class13.html (250 words)

	help.html
		The 'log P BBTM/Non-BBTM protein ratio' or 'log likelihood ratio' gives the log of the probability for seeing a bbtm protein of at least score D and the probability of seeing a non-bbtm protein of score D or greater i.e.
		The E-value returns the number of non-bbtm proteins which would be expected at a given discrimination score, given the number of sequences submitted i.e.
	www.bioinformatics.leeds.ac.uk /~andy/betaBarrel/AACompPred/help.html (245 words)

	Planar approximating method for computing the log-likelihood ratio optimal signal metric of each component code decoder in 8-PSK block coded modulation systems - Patent 5657354
		For decoding purposes, the optimum signal metric is the log likelihood ratio for this constellation.
		The ratio ##EQU7## is an estimate of the additional noise to signal ratio due to the log likelihood ratio planar approximation.
		In 8-PSK, as in the constellation in FIG.
	www.freepatentsonline.com /5657354.html (6638 words)

	Model-based voice activity detection system and method using a log-likelihood ratio and pitch - US Patent 6615170
		The dependency on empirically determined thresholds is removed as the log-likelihood ratio considers similarity measurements from both speech and silence templates.
		The frames of the input data are tagged based on the log-likelihood ratio test statistic and pitch characteristics of the input data as being most likely noise or most likely speech.
		For computational consideration and simplicity, a log-likelihood ratio test (LLRT) statistic or cepstrum is then defined as:
	www.patentstorm.us /patents/6615170.html (5393 words)

	Maximum Likelihood Workshop
		Log-likelihood ratio test statistic for F81 versus HKY (2(lnL1-lnL0)): ________
		In the case of nested models, twice the ratio of the likelihoods is Chi-squared distributed, where the degrees of freedom are equal to the difference in the number of parameters in the two models.
		Estimating likelihood in phylogenetic analysis can require a lot of computer memory because the probability of observing each nucleotide (A, G, C and T) at every position in the sequence must be calculated for every node in a given phylogeny.
	www.msu.edu /course/zol/855/f01/workshop3.html (991 words)

	Svenning, J.C. (1999) Microhabitat dependency in a species-rich palm community in Amazonian Equador. Journal of Ecology, 87, 55 - 65.
		The first was an overall test of significance using the log likelihood ratio chi-square test, which compares the full model to a model with just a constant.
		The second, a single effect test, which is the significance of each explanatory variable in the model judged individually by a log likelihood ratio chi-square test comparing the model with the model with just that variable deleted.
		The P-value for the whole-model likelihood ratio test is given at WM-P. The intercept is given at I. For a binary variable the value pertains to the state given in brackets after the variable abbreviation.
	www.blackwellpublishing.com /products/journals/suppmat/jec/arc13.htm (545 words)

	Cluster BusterData
		To evaluate the log likelihood ratio for all subsequences, it would be necessary to repeat the Forward algorithm once for each possible start point, requiring time proportional to the sequence lengh squared, which is not feasible for sequences longer than a few kb.
		The so-called Forward algorithm can calculate this log likelihood ratio for all prefixes 1..j, in time proportional to the sequence length.
		Cluster-Buster uses a linear-time heuristic which attempts to return the same motif cluster predictions as the full quadratic-time algorithm.
	zlab.bu.edu /cluster-buster/data.html (252 words)

	Asymptotics for likelihood ratio tests under loss of identifiability, Xin Liu, Yongzhao Shao
		This paper establishes a general quadratic approximation of the log-likelihood ratio function in a Hellinger neighborhood of the true density which is valid with or without loss of identifiability of the true distribution.
		It is well known that the classical asymptotic theory for the likelihood ratio test does not apply to such problems and the LRTS may not have the typical chi-squared type limiting distribution.
		This paper describes the large sample properties of the likelihood ratio test statistic (LRTS) when the parameters characterizing the true null distribution are not unique.
	projecteuclid.org /Dienst/UI/1.0/Display/euclid.aos/1056562463 (479 words)

	Detection of Quantitative Trait Loci Affecting Caffeine Metabolism by Interval Mapping in a Genome-Wide Scan of C3H/HeJ x APN F2 Mice -- Casley et al. 27 (12): 1375 -- Drug Metabolism and Disposition
		LOD scores are the logarithm of the ratio of the
		Kalow W and Tang BK (1991) Use of caffeine metabolite ratios to explore CYP1A2 and xanthine oxidase activities.
		ratio is one such index of this activity.
	dmd.aspetjournals.org /cgi/content/full/27/12/1375 (4553 words)

	Definition: Fagan nomogram
		And since multiplication of two numbers is equivalent to adding their logarithms, we use a log scaling for both the odds and the likelihood ratio.
		For technical reasons.we have to set the scaling of the log likelihood ratio to 1/2 that of the log odds.
		A study of an early test for developmetnal dysplasia of the hip (AJPH 1998; 88(2): 285-288) computed a likelihood ratio for a positive result as 7 for boys (5 for girls).
	www.cmh.edu /stats/definitions/fagan.htm (567 words)

	Likelihood Ratio Test
		The MCSE here is understated, since it only estimates the error of the log likelihood ratio assuming the two parameter values being compared are known.
		The likelihood ratio test is harder to calculate and cannot be done using samples from one model.
		Having estimated the normalizing constants, the likelihood ratio test statistic is
	www.stat.umn.edu /PAPERS/html_prints/points/node60.html (449 words)

	New Page 1
		The objective function is based on the statistical significance of the log likelihood ratio (LLR) of the occurrences of the motif.
		The E-value of the motif is an estimate of the number of motifs (with the same width and number of occurrences) that would have equal or higher log likelihood ratio if the training set sequences had been generated randomly according to the (0-order portion of the) background model.
		The E-value reported by MEME is actually an approximation of the E-value of the log likelihood ratio.
	faculty-staff.ou.edu /R/Thomas.S.Ray-1.Jr/Bioinformatics/software/meme.htm (3427 words)

	Analysis of Frequency Data in CoStat (Including Cross Tabulation, Calculating Expected Values, Goodness-Of-Fit Tests, Tests of Independence, Chi-Square, Likelihood Ratio, Log-Linear, and Fisher's Exact Test)
		Analysis of Frequency Data in CoStat (Including Cross Tabulation, Calculating Expected Values, Goodness-Of-Fit Tests, Tests of Independence, Chi-Square, Likelihood Ratio, Log-Linear, and Fisher's Exact Test)
		Williams' Correction for the Likelihood Ratio test (for intrinsic and extrinsic hypotheses) is used because it leads to a closer approximation of a chi-square distribution.
		Test the independence (the lack of interaction) of the two factors with the Chi-Square test, the Likelihood Ratio test, and Fisher's Exact Test.
	www.cohort.com /costatfrequency.html (1349 words)

	MATLAB Central - Newsreader - Log Likelihood - Statistics Toolbox
		Twice the log of the ratio of the larger likelihood to the smaller (twice
		I guess you are asking how you should use these log likelihood values.
		What do you mean by 'the closer the log likelihood is to unity the better'?
	newsreader.mathworks.com /WebX?14@1008.AQruamIi51P.0@.ef125e2 (975 words)

	lrlogit.hlp
		^lrglobal()^ asks for the overall likelihood ratio to be created and stored in the named variable.
		Options governing output ------------------------ ^lrname()^ asks for the likelihood ratios to be created and stored with the specified prefix.
		^replace^ specifies that the likelihood ratio variables may already exist.
	www.mrc-bsu.cam.ac.uk /pub/software/stata/lrlogit.hlp (612 words)

	3.4 Likelihood ratio test
		The higher the signal-to-noise ratio the higher the probability of detection.
		An interesting property of the matched filter is that it maximizes the signal-to-noise ratio over all linear filters [28].
		is the ratio of the pdf when the signal is present to the pdf when it is absent:
	www.emis.de /journals/LRG/Articles/lrr-2005-3/articlesu4.html (256 words)

	dnaMining :: CASP 2000 Abstract
		Statistical theory tells us that the log-likelihood ratio is the best method for distinguishing between two known statistical models.
		The conventional approach to homology searching, whether using the Smith-Waterman algorithm (including generalizations to HMMs) or heuristic approximations to it (such as Blast or FASTA), relies ultimately on a log-likelihood ratio for ranking the importance of the matches.
		Preliminary results show that our approach can detect more distant protein homologs than can be detected using PSI-Blast.
	www.dnamining.com /Pages/products1.html (413 words)

	R: Empirical likelihood ratio for mean with right, left or doubly censored data, by EM algorithm
		The -2 Log empirical likelihood ratio should be infinite.
		Empirical likelihood ratio for mean with right, left or doubly censored data, by EM algorithm
		In other cases, you have to plot a curve with many values of the parameter, mu, to find out where is the place the log likelihood becomes maximum.
	www.matematik.lu.se /help/R/.R/library/emplik/html/el.cen.EM.html (561 words)

	CEP: discussion papers
		Also, a bootstrap empirical log-likelihood ratio is derived and its distribution is used to approximate that of the imputed empirical log-likelihood ratio.
		An adjusted empirical log-likelihood ratio, which is asymptotically standard chi-square, is obtained.
		A simulation study is conducted to compare the adjusted and bootstrap empirical likelihood with the normal approximation-based method in terms of coverage accuracies and average lengths of confidence intervals.
	cep.lse.ac.uk /pubs/abstract.asp?index=1895 (239 words)

	Fine Mapping of a Quantitative Trait Locus for Twinning Rate Using Combined Linkage and Linkage Disequilibrium Mapping -- Meuwissen et al. 161 (1): 373 -- Genetics
		Log-likelihood ratio of linkage disequilibrium analysis (a) or linkage analysis (b).
		Log-likelihood ratio of combined linkage disequilibrium and linkage analysis.
		The distinct peak in the ninth bracket and the flat likelihood
	www.genetics.org /cgi/content/full/161/1/373 (3427 words)

	omodel.hlp
		The ratio is tested on degrees of freedom that are the difference between the number of fitted parameters in the standard and general models.
		Hence in taking the difference between the two approximations we obtain a reasonable approximation to the true lieklihood-ratio test.
		This will typically be (p)*(K-2), where p is the number of regressors specified, although under certain sparse data conditions there will be fewer degrees of freedom (see the second example above).
	www.stata.com /stb/stb42/sg76/omodel.hlp (424 words)

	Invariance Properties and Performance Evaluation of Bit Decoding Algorithms (SMEALSearch) - Pal,Rangaswamy,Giles,Debnath
		It is also shown that the pdf of a given bit LLR, when the corresponding bit takes the values of zero and one, are symmetric with respect to each other (reflection of one another with respect to the vertical axis).
		It is proved that under a set of mild conditions on the channel, the pdf of the bit LLR of a specific bit position is independent of the transmitted code-word.
		A general channel model with discrete (not necessarily binary) input and discrete or continuous output is considered.
	smealsearch.psu.edu /114776.html (453 words)

	Modeling Dependencies in Protein-DNA Binding Sites: Statistical Significance of Binding Sites
		To score a given K-mer we use the log likelihood ratio between the binding model and the background model.
		Using this scheme, a very large pool of K-mers is sampled from the background distribution, then each K-mer is scored according to its log-likelihood ratio.
		It does so by sampling from a different distribution Q() over the K-mers, and weighting the samples according to their likelihood ratio between the background distribution and Q().
	www.cs.huji.ac.il /labs/compbio/TFBN/PVal (645 words)

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