ESS — Emacs Speaks Statistics
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Emacspeak — the Complete Audio Desktop User Manual
Emacspeak | The Complete Audio Desktop User Manual T. V. Raman Last Updated: 19 November 2016 Copyright c 1994{2016 T. V. Raman. All Rights Reserved. Permission is granted to make and distribute verbatim copies of this manual without charge provided the copyright notice and this permission notice are preserved on all copies. Short Contents Emacspeak :::::::::::::::::::::::::::::::::::::::::::::: 1 1 Copyright ::::::::::::::::::::::::::::::::::::::::::: 2 2 Announcing Emacspeak Manual 2nd Edition As An Open Source Project ::::::::::::::::::::::::::::::::::::::::::::: 3 3 Background :::::::::::::::::::::::::::::::::::::::::: 4 4 Introduction ::::::::::::::::::::::::::::::::::::::::: 6 5 Installation Instructions :::::::::::::::::::::::::::::::: 7 6 Basic Usage. ::::::::::::::::::::::::::::::::::::::::: 9 7 The Emacspeak Audio Desktop. :::::::::::::::::::::::: 19 8 Voice Lock :::::::::::::::::::::::::::::::::::::::::: 22 9 Using Online Help With Emacspeak. :::::::::::::::::::: 24 10 Emacs Packages. ::::::::::::::::::::::::::::::::::::: 26 11 Running Terminal Based Applications. ::::::::::::::::::: 45 12 Emacspeak Commands And Options::::::::::::::::::::: 49 13 Emacspeak Keyboard Commands. :::::::::::::::::::::: 361 14 TTS Servers ::::::::::::::::::::::::::::::::::::::: 362 15 Acknowledgments.::::::::::::::::::::::::::::::::::: 366 16 Concept Index :::::::::::::::::::::::::::::::::::::: 367 17 Key Index ::::::::::::::::::::::::::::::::::::::::: 368 Table of Contents Emacspeak :::::::::::::::::::::::::::::::::::::::::: 1 1 Copyright ::::::::::::::::::::::::::::::::::::::: -
Sweave User Manual
Sweave User Manual Friedrich Leisch and R-core June 30, 2017 1 Introduction Sweave provides a flexible framework for mixing text and R code for automatic document generation. A single source file contains both documentation text and R code, which are then woven into a final document containing • the documentation text together with • the R code and/or • the output of the code (text, graphs) This allows the re-generation of a report if the input data change and documents the code to reproduce the analysis in the same file that contains the report. The R code of the complete 1 analysis is embedded into a LATEX document using the noweb syntax (Ramsey, 1998) which is usually used for literate programming Knuth(1984). Hence, the full power of LATEX (for high- quality typesetting) and R (for data analysis) can be used simultaneously. See Leisch(2002) and references therein for more general thoughts on dynamic report generation and pointers to other systems. Sweave uses a modular concept using different drivers for the actual translations. Obviously different drivers are needed for different text markup languages (LATEX, HTML, . ). Several packages on CRAN provide support for other word processing systems (see Appendix A). 2 Noweb files noweb (Ramsey, 1998) is a simple literate-programming tool which allows combining program source code and the corresponding documentation into a single file. A noweb file is a simple text file which consists of a sequence of code and documentation segments, called chunks: Documentation chunks start with a line that has an at sign (@) as first character, followed by a space or newline character. -
Emacspeak User's Guide
Emacspeak User's Guide Jennifer Jobst Revision History Revision 1.3 July 24,2002 Revised by: SDS Updated the maintainer of this document to Sharon Snider, corrected links, and converted to HTML Revision 1.2 December 3, 2001 Revised by: JEJ Changed license to GFDL Revision 1.1 November 12, 2001 Revised by: JEJ Revision 1.0 DRAFT October 19, 2001 Revised by: JEJ This document helps Emacspeak users become familiar with Emacs as an audio desktop and provides tutorials on many common tasks and the Emacs applications available to perform those tasks. Emacspeak User's Guide Table of Contents 1. Legal Notice.....................................................................................................................................................1 2. Introduction.....................................................................................................................................................2 2.1. What is Emacspeak?.........................................................................................................................2 2.2. About this tutorial.............................................................................................................................2 3. Before you begin..............................................................................................................................................3 3.1. Getting started with Emacs and Emacspeak.....................................................................................3 3.2. Emacs Command Conventions.........................................................................................................3 -
Emacs Speaks Statistics (ESS): a Multi-Platform, Multi-Package Intelligent Environment for Statistical Analysis
Emacs Speaks Statistics (ESS): A multi-platform, multi-package intelligent environment for statistical analysis A.J. Rossini Richard M. Heiberger Rodney A. Sparapani Martin Machler¨ Kurt Hornik ∗ Date: 2003/10/22 17:34:04 Revision: 1.255 Abstract Computer programming is an important component of statistics research and data analysis. This skill is necessary for using sophisticated statistical packages as well as for writing custom software for data analysis. Emacs Speaks Statistics (ESS) provides an intelligent and consistent interface between the user and software. ESS interfaces with SAS, S-PLUS, R, and other statistics packages under the Unix, Microsoft Windows, and Apple Mac operating systems. ESS extends the Emacs text editor and uses its many features to streamline the creation and use of statistical software. ESS understands the syntax for each data analysis language it works with and provides consistent display and editing features across packages. ESS assists in the interactive or batch execution by the statistics packages of statements written in their languages. Some statistics packages can be run as a subprocess of Emacs, allowing the user to work directly from the editor and thereby retain a consistent and constant look- and-feel. We discuss how ESS works and how it increases statistical programming efficiency. Keywords: Data Analysis, Programming, S, SAS, S-PLUS, R, XLISPSTAT,STATA, BUGS, Open Source Software, Cross-platform User Interface. ∗A.J. Rossini is Research Assistant Professor in the Department of Biostatistics, University of Washington and Joint Assis- tant Member at the Fred Hutchinson Cancer Research Center, Seattle, WA, USA mailto:[email protected]; Richard M. -
An Introduction to ESS + Xemacs for Windows Users of R
An Introduction to ESS + XEmacs for Windows Users of R John Fox∗ McMaster University Revised: 23 January 2005 1WhyUseESS+XEmacs? Emacs is a powerful and widely used programmer’s editor. One of the principal attractions of Emacs is its programmability: Emacs can be adapted to provide customized support for program- ming languages, including such features as delimiter (e.g., parenthesis) matching, syntax highlight- ing, debugging, and version control. The ESS (“Emacs Speaks Statistics”) package provides such customization for several common statistical computing packages and programming environments, including the S family of languages (R and various versions of S-PLUS), SAS, and Stata, among others. The current document introduces the use of ESS with R running under Microsoft Windows. For some Unix/Linux users, Emacs is more a way of life than an editor: It is possible to do almost everything from within Emacs, including, of course, programming, but also writing documents in mark-up languages such as HTML and LATEX; reading and writing email; interacting with the Unix shell; web browsing; and so on. I expect that this kind of generalized use of Emacs will not be attractive to most Windows users, who will prefer to use familiar, and specialized, tools for most of these tasks. There are several versions of the Emacs editor, the two most common of which are GNU Emacs, a product of the Free Software Foundation, and XEmacs, an offshoot of GNU Emacs. Both of these implementations are free and are available for most computing platforms, including Windows. In my opinion, based only on limited experience, XEmacs offers certain advantages to Windows users, such as easier installation, and so I will explain the use of ESS under this version of the Emacs editor.1 As I am writing this, there are several Windows programming editors that have been customized for use with R. -
Texing in Emacs Them
30 TUGboat, Volume 39 (2018), No. 1 TEXing in Emacs them. I used a simple criterion: Emacs had a nice tutorial, and Vim apparently did not (at that time). Marcin Borkowski I wince at the very thought I might have chosen Abstract wrong! And so it went. I started with reading the In this paper I describe how I use GNU Emacs to manual [8]. As a student, I had a lot of free time work with LAT X. It is not a comprehensive survey E on my hands, so I basically read most of it. (I still of what can be done, but rather a subjective story recommend that to people who want to use Emacs about my personal usage. seriously.) I noticed that Emacs had a nice TEX In 2017, I gave a presentation [1] during the joint mode built-in, but also remembered from one of GUST/TUG conference at Bachotek. I talked about the BachoTEXs that other people had put together my experiences typesetting a journal (Wiadomo´sci something called AUCTEX, which was a TEX-mode Matematyczne, a journal of the Polish Mathematical on steroids. Society), and how I utilized LAT X and GNU Emacs E In the previous paragraph, I mentioned modes. in my workflow. After submitting my paper to the In order to understand what an Emacs mode is, let proceedings issue of TUGboat, Karl Berry asked me me explain what this whole Emacs thing is about. whether I'd like to prepare a paper about using Emacs with LATEX. 1 Basics of Emacs Well, I jumped at the proposal. -
The Pretzel User Manual
The PretzelBook second edition Felix G¨artner June 11, 1998 2 Contents 1 Introduction 5 1.1 Do Prettyprinting the Pretzel Way . 5 1.2 History . 6 1.3 Acknowledgements . 6 1.4 Changes to second Edition . 6 2 Using Pretzel 7 2.1 Getting Started . 7 2.1.1 A first Example . 7 2.1.2 Running Pretzel . 9 2.1.3 Using Pretzel Output . 9 2.2 Carrying On . 10 2.2.1 The Two Input Files . 10 2.2.2 Formatted Tokens . 10 2.2.3 Regular Expressions . 10 2.2.4 Formatted Grammar . 11 2.2.5 Prettyprinting with Format Instructions . 12 2.2.6 Formatting Instructions . 13 2.3 Writing Prettyprinting Grammars . 16 2.3.1 Modifying an existing grammar . 17 2.3.2 Writing a new Grammar from Scratch . 17 2.3.3 Context Free versus Context Sensitive . 18 2.3.4 Available Grammars . 19 2.3.5 Debugging Prettyprinting Grammars . 19 2.3.6 Experiences . 21 3 Pretzel Hacking 23 3.1 Adding C Code to the Rules . 23 3.1.1 Example for Tokens . 23 3.1.2 Example for Grammars . 24 3.1.3 Summary . 25 3.1.4 Tips and Tricks . 26 3.2 The Pretzel Interface . 26 3.2.1 The Prettyprinting Scanner . 27 3.2.2 The Prettyprinting Parser . 28 3.2.3 Example . 29 3.3 Building a Pretzel prettyprinter by Hand . 30 3.4 Obtaining a Pretzel Prettyprinting Module . 30 3.4.1 The Prettyprinting Scanner . 30 3.4.2 The Prettyprinting Parser . 31 3.5 Multiple Pretzel Modules in the same Program . -
Using GNU Make to Manage the Workflow of Data Analysis Projects
JSS Journal of Statistical Software June 2020, Volume 94, Code Snippet 1. doi: 10.18637/jss.v094.c01 Using GNU Make to Manage the Workflow of Data Analysis Projects Peter Baker University of Queensland Abstract Data analysis projects invariably involve a series of steps such as reading, cleaning, summarizing and plotting data, statistical analysis and reporting. To facilitate repro- ducible research, rather than employing a relatively ad-hoc point-and-click cut-and-paste approach, we typically break down these tasks into manageable chunks by employing sep- arate files of statistical, programming or text processing syntax for each step including the final report. Real world data analysis often requires an iterative process because many of these steps may need to be repeated any number of times. Manually repeating these steps is problematic in that some necessary steps may be left out or some reported results may not be for the most recent data set or syntax. GNU Make may be used to automate the mundane task of regenerating output given dependencies between syntax and data files. In addition to facilitating the management of and documenting the workflow of a complex data analysis project, such automation can help minimize errors and make the project more reproducible. It is relatively simple to construct Makefiles for small data analysis projects. As projects increase in size, difficulties arise because GNU Make does not have inbuilt rules for statistical and related software. Without such rules, Makefiles can become unwieldy and error-prone. This article addresses these issues by providing GNU Make pattern rules for R, Sweave, rmarkdown, SAS, Stata, Perl and Python to streamline management of data analysis and reporting projects. -
Free As in Freedom (2.0): Richard Stallman and the Free Software Revolution
Free as in Freedom (2.0): Richard Stallman and the Free Software Revolution Sam Williams Second edition revisions by Richard M. Stallman i This is Free as in Freedom 2.0: Richard Stallman and the Free Soft- ware Revolution, a revision of Free as in Freedom: Richard Stallman's Crusade for Free Software. Copyright c 2002, 2010 Sam Williams Copyright c 2010 Richard M. Stallman Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled \GNU Free Documentation License." Published by the Free Software Foundation 51 Franklin St., Fifth Floor Boston, MA 02110-1335 USA ISBN: 9780983159216 The cover photograph of Richard Stallman is by Peter Hinely. The PDP-10 photograph in Chapter 7 is by Rodney Brooks. The photo- graph of St. IGNUcius in Chapter 8 is by Stian Eikeland. Contents Foreword by Richard M. Stallmanv Preface by Sam Williams vii 1 For Want of a Printer1 2 2001: A Hacker's Odyssey 13 3 A Portrait of the Hacker as a Young Man 25 4 Impeach God 37 5 Puddle of Freedom 59 6 The Emacs Commune 77 7 A Stark Moral Choice 89 8 St. Ignucius 109 9 The GNU General Public License 123 10 GNU/Linux 145 iii iv CONTENTS 11 Open Source 159 12 A Brief Journey through Hacker Hell 175 13 Continuing the Fight 181 Epilogue from Sam Williams: Crushing Loneliness 193 Appendix A { Hack, Hackers, and Hacking 209 Appendix B { GNU Free Documentation License 217 Foreword by Richard M. -
Species' Traits and Phylogenetic
Northern Michigan University NMU Commons All NMU Master's Theses Student Works 8-2018 CLIMATE DRIVEN RANGE SHIFTS OF NORTH AMERICAN SMALL MAMMALS: SPECIES’ TRAITS AND PHYLOGENETIC INFLUENCES Katie Nehiba [email protected] Follow this and additional works at: https://commons.nmu.edu/theses Part of the Ecology and Evolutionary Biology Commons Recommended Citation Nehiba, Katie, "CLIMATE DRIVEN RANGE SHIFTS OF NORTH AMERICAN SMALL MAMMALS: SPECIES’ TRAITS AND PHYLOGENETIC INFLUENCES" (2018). All NMU Master's Theses. 557. https://commons.nmu.edu/theses/557 This Open Access is brought to you for free and open access by the Student Works at NMU Commons. It has been accepted for inclusion in All NMU Master's Theses by an authorized administrator of NMU Commons. For more information, please contact [email protected],[email protected]. CLIMATE DRIVEN RANGE SHIFTS OF NORTH AMERICAN SMALL MAMMALS: SPECIES’ TRAITS AND PHYLOGENETIC INFLUENCES By Katie R. Nehiba THESIS Submitted to Northern Michigan University In partial fulfillment of the requirements For the degree of MASTER OF SCIENCE Office of Graduate Education and Research July 2018 ABSTRACT By Katie R. Nehiba Current anthropogenically-driven climate change is accelerating at an unprecedented rate. In response, species’ ranges may shift, tracking optimal climatic conditions. Species-specific differences may produce predictable differences in the extent of range shifts. I evaluated if patterns of predicted responses to climate change were strongly related to species’ taxonomic identities and/or ecological characteristics of species’ niches, elevation and precipitation. I evaluated differences in predicted range shifts in well-sampled small mammals that are restricted to North America: kangaroo rats, voles, chipmunks, and ground squirrels. -
Living in Emacs the Basics of Using Emacs
Living in Emacs The basics of using Emacs Skill Level: Introductory Brian Bilbrey ([email protected]) System administrator Freelance 02 Jul 2002 This tutorial is your guide to the basics of using Emacs, a popular modeless text editor with many powerful features. The tutorial covers fundamental concepts and common activities, and then builds on those foundations to quickly familiarize you with this excellent editor. Section 1. Before you start About this tutorial This tutorial gives you a guide to the basics of using Emacs, a popular modeless text editor with many powerful features. The tutorial covers fundamental concepts and common activities, and then builds on those foundations to quickly familiarize you with this excellent editor. Getting started with Emacs requires navigating a steep learning curve. Our goal is to help you past the initially unfamiliar interface so that the power and utility of Emacs become apparent. Then you'll be ready to explore further on your own, following up on the resources and tips at the end of the tutorial. The primary users of Emacs are programmers and Web developers who want to get the most out of this powerful and flexible text editor and thereby increase their productivity. Additionally, at least a passing familiarity with Emacs is useful for anyone who performs administrative duties in UNIX or similar environments. Living in Emacs © Copyright IBM Corporation 1994, 2008. All rights reserved. Page 1 of 22 developerWorks® ibm.com/developerWorks Prerequisites All you need to work through this tutorial is a copy of Emacs, either GNU Emacs or XEmacs. If you're running Linux, then you might already have it loaded. -
Reproducible Research.. Using Sweave, Knitr and Pandoc
Reproducible Research.. Using Sweave, Knitr and Pandoc Aedín Culhane [email protected] Nov 20th 2012 My R Course Website http://bcb.dfci.harvard.edu/~aedin/ My HSPH homepage http://www.hsph.harvard.edu/research/aedin-culhane/ When issues of reproducibility arise • ``Remember that microarray analysis you did six months ago? We ran a few more arrays. Can you add them to the project and repeat the same analysis?'' • ``The statistical analyst who looked at the data I generated previously is no longer available. Can you get someone else to analyze my new data set using the same methods (and thus producing a report I can expect to understand)?'' • ``Please write/edit the methods sections for the abstract/paper/grant proposal I am submitting based on the analysis you did several months ago.'' From Keith Baggerly • Selected articles published in Nature Genetics between January 2005 and December 2006 that had used profiling with microarrays • Of the 56 items retrieved electronically, 20 articles were considered potentially eligible for the project • The four teams were from – University of Alabama at Birmingham (UAB) – Stanford/Dana-Farber (SD) – London (L) and Ioannina/Trento (IT) • Each team was comprised of 3-6 scientists who worked together to evaluate each article. Results • Result could be reproduced n=2 • Reproduced with discrepancy n=6 • Could not be reproduced n=10 – No data n=4 (no data n=2, subset n=1, no reporter data n=1) – Confusion over matching of data to analysis (n=2) – Specialized software required and not available (n=1)m – Raw data available but could not be processed n=2 Reproducibility of Analysis Ioannidis JP, Allison DB, Ball CA, Coulibaly I, Cui X, Culhane AC, et al, (2009) Repeatability of published microarray gene expression Analyses.