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Lfe: Linear Group Fixed Effects, Simen Gaure 2013 Ragnar Frisch Centre for Economic Research

Lfe: Linear Group Fixed Effects, Simen Gaure

The R Journal

Linear models with fixed effects and many dummy variables are common in some fields. Such models are straightforward to estimate unless the factors have too many levels. The R package lfe solves this problem by implementing a generalization of the within transformation to multiple factors, tailored for large problems.


Complognormal: An R Package For Composite Lognormal Distributions, S. Nadarajah, S. A.A. Bakar 2013 University of Manchester

Complognormal: An R Package For Composite Lognormal Distributions, S. Nadarajah, S. A.A. Bakar

The R Journal

In recent years, composite models based on the lognormal distribution have become popular in actuarial sciences and related areas. In this short note, we present a new R package for computing the probability density function, cumulative density function, and quantile function, and for generating random numbersof anycomposite model based on the lognormal distribution. The use of the package is illustrated using a real data set.


Temporal Disaggregation Of Time Series, Christoph Sax, Peter Steiner 2013 University of Basel

Temporal Disaggregation Of Time Series, Christoph Sax, Peter Steiner

The R Journal

Temporal disaggregation methods are used to disaggregate low frequency time series to higher frequency series, where either the sum, the average, the first or the last value of the resulting high frequency series is consistent with the low frequency series. Temporal disaggregation can be performed with or without one or more high frequency indicator series. The package tempdisagg is a collection of several methods for temporal disaggregation.


On Sampling From The Multivariate T Distribution, Marius Hofert 2013 ETH Zürich

On Sampling From The Multivariate T Distribution, Marius Hofert

The R Journal

The multivariate normal and the multivariate t distributions belong to the most widely used multivariate distributions in statistics, quantitative risk management, and insurance. In contrast to the multivariate normal distribution, the parameterization of the multivariate t distribution does not correspond to its moments. This, paired with a non-standard implementation in the R package mvtnorm, provides traps for working with the multivariate t distribution. In this paper, common traps are clarified and corresponding recent changes to mvtnorm are presented.


Performance Attribution For Equity Portfolios, Yang Lu, David Kane 2013 Williams College

Performance Attribution For Equity Portfolios, Yang Lu, David Kane

The R Journal

The pa package provides tools for conducting performance attribution for long-only, single currency equity portfolios. The package uses two methods: the Brinson-Hood-Beebower model (hereafter referred to as the Brinson model) and a regression-based analysis. The Brinson model takes an ANOVA-type approach and decomposes the active return of any portfolio into asset allocation, stock selection, and interaction effect. The regression-based analysis utilizes estimated coefficients, based on a regression model, to attribute active return to different factors.


Rlme: An R Package For Rank-Based Estimation And Prediction In Random Effects Nested Models, Yusuf K. Bilgic, Herbert Susmann 2013 SUNY Geneseo

Rlme: An R Package For Rank-Based Estimation And Prediction In Random Effects Nested Models, Yusuf K. Bilgic, Herbert Susmann

The R Journal

There is a lack of robust statistical analyses for random effects linear models. In practice, statistical analyses, including estimation, prediction and inference, are not reliable when data are unbalanced, of small size, contain outliers, or not normally distributed. It is fortunate that rank-based regression analysis is a robust nonparametric alternative to likelihood and least squares analysis. We propose an R package that calculates rank-based statistical analyses for two- and three-level random effects nested designs. In this package, a new algorithm which recursively obtains robust predictions for both scale and random effects is used, along with three rank-based fitting methods.


Factorplot: Improving Presentation Of Simple Contrasts In Generalized Linear Models, David A. Armstrong II 2013 University of Wisconsin- Milwaukee

Factorplot: Improving Presentation Of Simple Contrasts In Generalized Linear Models, David A. Armstrong Ii

The R Journal

Recent statistical literature has paid attention to the presentation of pairwise comparisons either from the point of view of the reference category problem in generalized linear models (GLMs) or in terms of multiple comparisons. Both schools of thought are interested in the parsimonious presentation of sufficient information to enable readers to evaluate the significance of contrasts resulting from the inclusion of qualitative variables in GLMs. These comparisons also arise when trying to interpret multinomial models where one category of the dependent variable is omitted as a reference. While considerable advances have been made, opportunities remain to improve the presentation of …


Exactcidiff: An R Package For Computing Exact Confidence Intervals For The Difference Of Two Proportions, Guogen Shan, Weizhen Wang 2013 University of Nevada Las Vegas,

Exactcidiff: An R Package For Computing Exact Confidence Intervals For The Difference Of Two Proportions, Guogen Shan, Weizhen Wang

The R Journal

Comparing two proportions through the difference is a basic problem in statistics and has applications in many fields. More than twenty confidence intervals (Newcombe, 1998a,b) have been proposed. Most of them are approximate intervals with an asymptotic infimum coverage probability much less than the nominal level. In addition, large sample may be costly in practice. So exact optimal confidence intervals become critical for drawing valid statistical inference with accuracy and precision. Recently, Wang (2010, 2012) derived the exact smallest (optimal) one-sided 1 confidence intervals for the difference of two paired or independent proportions. His intervals, however, are computer-intensive by nature. …


Rnetcdf: A Package For Reading And Writing Netcdf Datasets, Pavel Michna, Milton Woods 2013 Hallerstrasse 12

Rnetcdf: A Package For Reading And Writing Netcdf Datasets, Pavel Michna, Milton Woods

The R Journal

This paper describes the RNetCDF package (version 1.6), an interface for reading and writing files in Unidata NetCDF format, and gives an introduction to the NetCDF file format. NetCDF is a machine independent binary file format which allows storage of different types of array based data, along with short metadata descriptions. The package presented here allows access to the most important functions of the NetCDF C-interface for reading, writing, and modifying NetCDF datasets. In this paper, we present a short overview on the NetCDF file format and show usage examples of the package.


Spmc: Modelling Spatial Random Fields With Continuous Lag Markov Chains, Luca Sartore 2013 Università degli Studi di Padova

Spmc: Modelling Spatial Random Fields With Continuous Lag Markov Chains, Luca Sartore

The R Journal

Currently, a part of the R statistical software is developed in order to deal with spatial models. More specifically, some available packages allow the user to analyse categorical spatial random patterns. However, only the spMC package considers a viewpoint based on transition probabilities between locations. Through the use of this package it is possible to analyse the spatial variability of data, make inference, predict and simulate the categorical classes in unobserved sites. An example is presented by analysing the well-known Swiss Jura data set.


Betategarch: Simulation, Estimation And Forecasting Of Beta-Skew-T-Egarch Models, Genaro Sucarrat 2013 BI Norwegian Business School

Betategarch: Simulation, Estimation And Forecasting Of Beta-Skew-T-Egarch Models, Genaro Sucarrat

The R Journal

This paper illustrates the usage of the betategarch package, a package for the simulation, estimation and forecasting of Beta-Skew-t-EGARCH models. The Beta-Skew-t-EGARCH model is a dynamic model of the scale or volatility of financial returns. The model is characterised by its robustness to jumps or outliers, and by its exponential specification of volatility. The latter enables richer dynamics, since parameters need not be restricted to be positive to ensure positivity of volatility. In addition, the model also allows for heavy tails and skewness in the conditional return (i.e. scaled return), and for leverage and a time-varying long-term component in the …


Popcorn And A Movie: Using Popcorn.Js To Enhance Digital Collections, Sean Anderson, Adam C. Northam 2013 Texas A&M University-Commerce

Popcorn And A Movie: Using Popcorn.Js To Enhance Digital Collections, Sean Anderson, Adam C. Northam

Velma K. Waters Library Faculty Publications

No abstract provided.


Changes On Cran, Kurt Hornik, Achim Zeileis 2013 WU Wirtschaftsuniversität Wien

Changes On Cran, Kurt Hornik, Achim Zeileis

The R Journal

New CRAN task views

New packages in CRAN task views

New contributed packages

Other changes


Changes In R, The R Core Team 2013 University of Nebraska - Lincoln

Changes In R, The R Core Team

The R Journal

CHANGES IN R 3.0.2


News From The Bioconductor Project, Bioconductor Team 2013 Bioconductor Team

News From The Bioconductor Project, Bioconductor Team

The R Journal

Bioconductor 2.13 was released on 15 October2013. It is compatible with R3.0.2, and consists of 749 software packages, 179 experiment data packages, and more than 690 up-to-date annotation packages. The release includes 84 new software packages, and enhancements to many others. Descriptions of new packages and updated NEWS files provided by current package maintainers are at http://bioconductor.org/news/bioc_2_13_release/


Surface Melting Curve Analysis With R, Stefan Rödiger, Alexander Böhm, Ingolf Schimke 2013 Charité-Universitätsmedizin Berlin, Lausitz University of Applied Sciences

Surface Melting Curve Analysis With R, Stefan Rödiger, Alexander Böhm, Ingolf Schimke

The R Journal

Nucleic acid Melting Curve Analysis is a powerful method to investigate the interaction of double stranded nucleic acids. Many researchers rely on closed source software which is not ubiquitously available, and gives only little control over the computation and data presentation. R in contrast, is open source, highly adaptable and provides numerous utilities for data import, sophisticated statistical analysis and presentation in publication quality. This article covers methods, implemented in the MBmca package, for DNA Melting Curve Analysis on microbead surfaces. Particularly, the use of the second derivative melting peaks is suggested as an additional parameter to characterize the melting …


The R In Robotics, André Dietrich, Sebastian Zug, Jörg Kaiser 2013 Otto-von-Guericke-Universität Magdeburg

The R In Robotics, André Dietrich, Sebastian Zug, Jörg Kaiser

The R Journal

The aim of this contribution is to connect two previously separated worlds: robotic application development with the Robot Operating System (ROS) and statistical programming with R. This fruitful combination becomes apparent especially in the analysis and visualization of sensory data. We therefore introduce a new language extension for ROS that allows to implement nodes in pure R. All relevant aspects are described in a step-by-step development of a common sensor data transformation node. This includes the reception of raw sensory data via the ROS network, message interpretation, bag-file analysis, transformation and visualization, as well as the transmission of newly generated …


Editorial, Hadley Wickham 2013 RStudio

Editorial, Hadley Wickham

The R Journal

Welcome to volume 5, issue 2 of The R Journal. I’m very pleased to include 21 articles about R for your enjoyment.

The end of the year also brings changes to the editorial board. Martyn Plummer is leaving the board after four years. Martyn was responsible for writing up the standard operating procedures for the journal, an act which has made my life as a new editor considerably easier! We welcome Michael Lawrence, who will join the editorial board in 2014. I am stepping down as Editor-in-Chief and will be leaving this task in the capable hands of Deepayan Sarkar.


Understanding The Genetic Makeup Of Linux Device Drivers, Peter Senna Tschudin, Laurent Reveillere, Lingxiao JIANG, David LO, Julia Lawall 2013 SMU

Understanding The Genetic Makeup Of Linux Device Drivers, Peter Senna Tschudin, Laurent Reveillere, Lingxiao Jiang, David Lo, Julia Lawall

Research Collection School Of Computing and Information Systems

No abstract provided.


From Rssi To Csi: Indoor Localization Via Channel Response, Zheng YANG, Zimu ZHOU, Yunhao LIU 2013 Singapore Management University

From Rssi To Csi: Indoor Localization Via Channel Response, Zheng Yang, Zimu Zhou, Yunhao Liu

Research Collection School Of Computing and Information Systems

The spatial features of emitted wireless signals are the basis of location distinction and determination for wireless indoor localization. Available in mainstream wireless signal measurements, the Received Signal Strength Indicator (RSSI) has been adopted in vast indoor localization systems. However, it suffers from dramatic performance degradation in complex situations due to multipath fading and temporal dynamics.


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