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Package ‘forecast’ June 21, 2018 Version 8.4 Title Forecasting Functions for Time Series and Linear Models Description Methods and tools for displaying and analysing

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Package ‘segmented’ - R

Package ‘segmented’ November 30, 2017 Type Package Title Regression Models with Break-Points / Change-Points Estimation Version 0.5-3.0 Date 2017-11-22

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gap: Genetic Analysis Package - R

2 gap: Genetic Analysis Package from patients su ering with di erent diseases to identify common genetic variations for each condition. It is hoped that by identifying these genetic signposts, researchers will

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Package ‘season’ - R

Package ‘season’ May 20, 2018 Type Package Title Seasonal Analysis of Health Data Version 0.3.6 Author Adrian Barnett and Peter Baker Maintainer Adrian Barnett <a.barnett@qut.edu.au>

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Package ‘medicalrisk’ - The Comprehensive R …

Package ‘medicalrisk’ ... 2016 Type Package Title Medical Risk and Comorbidity Tools for ICD-9-CM Data Version 1.2 Date 2016-01-23 Description Generates risk estimates and comorbidity flags from ICD-9-CM ... Adapting a clinical comorbidity index for use with ICD-9-CM administrative data: differing perspectives. Journal of clinical ...

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Package ‘testthat’ - R

Package ‘testthat’ December 13, 2017 Title Unit Testing for R Version 2.0.0 Description Software testing is important, but, in part because it is

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Package ‘emma’ - R

2 emma-package Index 21 emma-package Designing experiments for process optimization Description The evolutionary model-based multiresponse approach (EMMA) is a procedure for process opti-

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Package ‘WeibullR’ - cran.r-project.org

Power" presentations in Appendix D of "The New Weibull Handbook, Fifth Edition". For validity of a 3rd parameter optimization on a given model over its 2 parameter fit, only the Likelihood Ratio Test will be applied. This validity check requires an LRT-P greater than 50 Value

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Package ‘maps’ - R

Package ‘maps’ April 3, 2018 Title Draw Geographical Maps Version 3.3.0 Date 2018-04-03 Author Original S code by Richard A. Becker and Allan R. Wilks.

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Chapter 11 Nonlinear Optimization Examples

Nonlinear Optimization Examples Overview The IML procedure offers a set of optimization subroutines for minimizing or max-imizing a continuous nonlinear function f = (x) of n parameters, where (x 1;::: ;x n) T. The parameters can be subject to boundary constraints and linear or nonlinear equality and inequality constraints. The following set of ...

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list of some useful R functions - Columbia University

{ o set: An o set is a term to be added to a linear predictor, such as in a generalised linear model Generalized Linear Models (GLM) { glm: is used to t generalized linear models ("stats") "family=" specify the details of the models used by glm ("stats") { glm.nb: t a negative binomial generalized linear model ("MASS") Diagnostics

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CHAPTER 8 Vehicle Nonlinear Equations ofMotion

CHAPTER 8 Vehicle Nonlinear Equations ofMotion A SIX DEGREE OF FREEDOM NONLINEAR VEHICLE MODEL is developed independently of the model used for the Berkeley simulation of Section 2 and described in (Peng 1992). This effort is a continuation of the work reported in (Douglas et al. 1995).

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Introduction to Applied Linear Algebra

The book covers less mathematics than a typical text on applied linear algebra. We use only one theoretical concept from linear algebra, linear independence, and only one computational tool, the QR factorization; our approach to most applica-tions relies on only one method, least squares (or some extension). In this sense

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Generalized Linear Models

15.1. The Structure of Generalized Linear Models 383 Here, ny is the observed number of successes in the ntrials, and n(1 −y)is the number of failures; and n ny = n! (ny)![n(1 −y)]! is the binomial coefficient. • The Poisson distributions are a discrete family with probability function indexed by the rate parameter μ>0: p(y)= μy × e−μ y

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Solving Applied Mathematical Problems with MATLAB

SOLVING APPLIED MATHEMATICAL PROBLEMS WITH MATLAB® Dingyü Xue YangQuan Chen C8250_FM.indd 3 9/19/08 4:21:15 PM