Parametric modeling

It is well known that occurrence counts of words in documents are often modeled poorly by standard distributions like the binomial or Poisson. Observed counts vary more than simple models predict, prompting the use of overdispersed models like GammaPoisson or Betabinomial mixtures as robust alternatives. Another deﬁciency of standard models is due to the fact that most words never occur in a given document, resulting in large amounts of zero counts. We propose using zeroinﬂated models for dealing with this, and evaluate competing models on a Naive Bayes text classiﬁcation task.
8p bunbo_1 17042013 14 2 Download

[ Team LiB ] 7.8 Generate Blocks Generate statements allow Verilog code to be generated dynamically at elaboration time before the simulation begins. This facilitates the creation of parametrized models
7p sieukidvn 16082010 43 3 Download

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Image Resolution Enhancement via DataDriven Parametric Models in the Wavelet Space
12p sting11 09032012 16 3 Download

Introduction to Creo Parametric 3.0 includes introduction to Creo Parametric 3.0; introduction to the Creo Parametric Basic Modeling Process; understanding Creo Parametric Concepts; using the Creo Parametric Interface; selecting Geometry, Features, and Models; editing Geometry, Features, and Models; creating Sketcher Geometry; using Sketcher Tools; creating Sketches for Features and some things else.
776p b1305467 02062015 55 33 Download

The goal of this course is to teach you how to use the SolidWorks mechanical design automation software to build parametric models of parts and assemblies and how to make simple drawings of those parts and assemblies.
506p ckm0789 11012014 84 26 Download

Sheetmetal Design using Creo Parametric 2.0 presents Sheetmetal Design using Creo Parametric 2.0; Sheetmetal Model Fundamentals; Creating Primary Sheetmetal Wall Features; Creating Secondary Sheetmetal Wall Features; Bending and Unbending Sheetmetal Models; Modifying Sheetmetal Models; Sheetmetal Setup and Tools; Detailing Sheetmetal Designs.
286p b1305467 02062015 36 15 Download

Linear parametric models of stationary random processes, whether signal or noise, have been found to be useful in a wide variety of signal processing tasks such as signal detection, estimation, filtering,
14p nguyen4 17112009 47 5 Download

We propose a nonparametric Bayesian model for unsupervised semantic parsing. Following Poon and Domingos (2009), we consider a semantic parsing setting where the goal is to (1) decompose the syntactic dependency tree of a sentence into fragments, (2) assign each of these fragments to a cluster of semantically equivalent syntactic structures, and (3) predict predicateargument relations between the fragments.
11p hongdo_1 12042013 15 3 Download

In this paper we propose a method for the automatic decipherment of lost languages. Given a nonparallel corpus in a known related language, our model produces both alphabetic mappings and translations of words into their corresponding cognates. We employ a nonparametric Bayesian framework to simultaneously capture both lowlevel character mappings and highlevel morphemic correspondences.
10p hongdo_1 12042013 13 2 Download

In this paper* I will argue for a model of grammatical processing that is based on uniform processing and knowledge sources. The main feature of this model is to view parsing and generation as two strongly interleaved tasks performed by a single parametrized deduction process. It will be shown that this view supports flexible and efficient natural language processing.
6p buncha_1 08052013 19 2 Download

This document includes: Measurement of efficiency, Mathematical programming models: the nonparametric approach, Stochastic frontier models: the parametric approach.
27p tunghai08 28062015 18 2 Download

The paper presents a language model that develops syntactic structure and uses it to extract meaningful information from the word history, thus enabling the use of long distance dependencies. The model assigns probability to every joint sequence of wordsbinaryparsestructure with headword annotation. The model, its probabilistic parametrization, and a set of experiments meant to evaluate its predictive power are presented.
3p bunthai_1 06052013 15 1 Download

The paper describes an experimental model of syntactic structure generation starting from the limited fragment of semantics that deals with the quantitative values of object parameters. To present the input information the basic semantic units of four types are proposed:"object", "parameter", "function" and "constant".
4p buncha_1 08052013 9 1 Download

Since the publication of my book Mathematical Statistics (Shao, 2003), I have been asked many times for a solution manual to the exercises in my book. Without doubt, exercises form an important part of a textbook on mathematical statistics, not only in training students for their research ability in mathematical statistics but also in presenting many additional results as complementary material to the main text.
384p crius75 02012013 112 55 Download

Chapter 13b: Answer key about COST MANAGEMENT 1. Answer: c Both the cost and accuracy of parametric models vary widely. They are most likely to be reliable when the historical information used to develop the model was accurate, the parameters used in the model are readily quantiﬁable, and the model is scalable (i.e., it works as well for a very large project as for a very small one). 2. Answer: b An analogous estimate is one that is arrived at by taking a project or part of a project that is already completed and adjusting the cost on the basis...
7p hoason23 17082010 86 45 Download

Knowing that the plant parameters can vary within their lower and upper bounds, this parametric uncertainty is formulated as an additive perturbation in the transfer function matrix. It is important to note that the controller be designed with respect to worst case uncertainty for each λij. This can be achieved by performing an optimization procedure given by (61) for 200 frequencies. Here an element by element uncertainty bound model is used for the characterization of upper bound of the uncertainty matrix. Then wij , which satisfies (62) for each λij is given in matrix form as,...
380p lulanphuong 22032012 98 34 Download

The Signal Processing Toolbox is a collection of tools built on the MATLAB® numeric computing environment. The toolbox supports a wide range of signal processing operations, from waveform generation to filter design and implementation, parametric modeling, and spectral analysis. The toolbox provides two categories of tools:
30p longtuyenthon 27012010 59 13 Download

Parametric representation of shapes, mechanical components modeling with 3D visualization techniques using object oriented programming, the well known golden ratio application on vertical and horizontal displacement investigations of the ground surface, spatial modeling and simulating of dynamic continuous fluid flow process, simulation model for wastewater treatment, an interaction of tilt and illumination conditions at flight simulation and errors in taxiing performance, plant layout optimal plot plan, atmospheric modeling for weather prediction, a stochastic search method that explores ...
312p kimngan_1 05112012 38 12 Download

This book provides a wealth of new information, ideas and analysis on some of the key unknowns in hurricane research.
206p crius75 02012013 34 9 Download

Estimation theory gives one approach to characterizing random variables. This was based on building parametric models and describing the data by the parameters. An alternative approach is given by information theory. Here the emphasis is on coding. We want to code the observations. The observations can then be stored in the memory of a computer, or transmitted by a communications channel, for example.
20p duongph05 09062010 76 7 Download