A generalised random current representation for O(n) models
Gradient test for generalised linear models with random effects.
... 2 Universidade Federal do Rio Grande do Norte, Natal, Brazil E-mail for correspondence: [email protected] Abstract: This work develops the gradient test for parameter selection in gen- eralised ...
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Generalised linear models
... simple plot of the binary variable can mask the density of points as points are overlaid on each other. Introducing a jitter, a random displacement of small magnitude to the binary points, enables better ...
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Generalised Random Binned Antenna Arrays
... continuos current (supported over the array aperture) that gives the desired radiation ...the random radiation pattern deviates from its ...the random radiation pattern is close to the average ...
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The representation of Northern Hemisphere blocking in current global climate models
... For the locally defined AGP index, defining the persistence of blocking at the grid-box scale is not meaningful and spatial 130 aggregation is necessary before the persistence analysis is carried out. We aggregate here ...
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GENERALISED MODELS FOR TORSIONAL SPINE RECONNECTION
... reconnection models when the current is restricted in which the Maxwell conditions are illumi- ...the current layers inside which torsional spine reconnection happen is autonomous on the symmetry of ...
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Generalised Design Models For EMS Maglev
... DESIGN O P Q L R S T U A V W W V X W Y V A A number of parameters are inevitably dictated by the specific details of the magnet design and so some consideration is necessary prior to populating the model with ...
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Generalised Bayesian matrix factorisation models
... non-parametric models are models on infinite dimen- sional parameter spaces, but which use only a finite subset of the parameter dimensions to explain a finite set of data (Orbanz and Teh, ...scale-mixture ...
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Phase transitions and the random cluster representation for Delaunay Potts models with geometry dependent interactions
... of models where the background interac- tion is strictly positive for all long-range ...key models we analyse for such geometry-dependence in the background ...These models are similar to those ...
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Analysis of generalised mixed models for categorical data
... The standard analysis of contingency tables or cross-classified categorical data are often performed under the assumption that observations which contribute to the category counts are independent. However, in many ...
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Effect Displays in R for Generalised Linear Models
... linear model. Fitted values under the model are computed for each such term. The lower-order ‘relatives’ of a high-order term (e.g., main effects marginal to an interaction) are absorbed into the term, allowing the ...
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Effect Displays in R for Generalised Linear Models
... linear model. Fitted values under the model are computed for each such term. The lower-order ‘relatives’ of a high-order term (e.g., main effects marginal to an interaction) are absorbed into the term, allowing the ...
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An ARMA Representation of Unobserved Component Models under Generalized Random Walk Specifications: New Algorithms and Examples
... 1 Introduction During the last two decades the literature on signal extraction has been roughly based on the so-called model-based approach. Three directions have emerged: (1) one, termed the ARIMA-model based or ...
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Fitting generalised linear models to car claims data
... y − = = The log link is the canonical link function for a random variable having a Poisson distribution η i = log µ i , implying that d i = ∂ η i ∂ µ i = 1 µ i . Given the fact that the mean and variance of y are ...
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Inference for generalised linear mixed models with sparse structure
... a generalised linear mixed ...a generalised linear mixed model, there is a parameter ψ controlling how the random effects enter into the linear ...no random effects in the ...
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Generalised additive multiscale wavelet models constructed using particle swarm optimisation and mutual information for spatio-temporal evolutionary system representation
... As will be seen from the illustrative example, by combining the PSO based nonlinear OPP learning method with the effective mutual information aided FOR algorithm, the resultant additive wavelet model can provide very ...
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On Delaunay random cluster models
... A −1 . Our estimates for these activity and temperature thresholds are similar to those in [BBD03], although the former depends on the angle threshold β 0 between discouraged and non-discouraged triangles in our case, ...
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Critical exponent omega at O(1/N) in O(N) x O(m) spin models
... in d = 4 − 2ǫ dimensions are in exact agreement with the perturbative coefficients in the renormalization group function to the perturbative order they are known, at a particular order in 1/N . More significantly ...
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Distributed representation and estimation of WFST based n gram models
... (WFST) representation of an n-gram language model into multiple blocks or shards, each of which is a stand-alone WFST n-gram model in its own right, allowing process- ing with existing ...large ...
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Statistical Representation of Grammaticality Judgements: the Limits of N Gram Models
... that n-gram mod- els have problems recognizing lexical dependen- cies that determine the felicitousness of passives constructed using ambiguous transitive verbs, as these are, for the most part, ...
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ALLEN O N O N N O N N
... Allen Ans. (D) Sol. Refer NCERT (Page No. 426) SECTION-B 1. CNG is an important transportation fuel. When 100 g CNG is mixed with 208 oxygen in vehicles, it leads to the formation of CO 2 and H 2 O and produces ...