“…Ce recueil explore les « (r)apports textuels » envisagés comme une érotique de l'écriture, tout autant que de la lecture, au fil des textes de grands écrivains de langue anglaise pour la plupart, de la Renaissance à nos jours, en passant par les précurseurs du postmodernisme américain. …”

Tabla de Contenidos: “…Daniels -- Grammar and language in syntactic structures: transformational progress and structuralist reflux / Pierre Swiggers -- Chomsky's other revolution / R. Allen Harris -- Chomsky between revolutions / Malcolm D. …”

“…R & D management (Online)…”

Tabla de Contenidos: “…An Introduction to R -- to Bayesian Thinking -- Single-Parameter Models -- Multiparameter Models -- to Bayesian Computation -- Markov Chain Monte Carlo Methods -- Hierarchical Modeling -- Model Comparison -- Regression Models -- Gibbs Sampling -- Using R to Interface with WinBUGS…”

Tabla de Contenidos: “…Introduction to Python R and data science -- Data input -- Data inspection and data quality -- Exploratory data analysis -- Statistical modeling -- Data visualization -- Machine learning made easier…”

Tabla de Contenidos: “…About SAS and R -- Data input, import and print -- Data inspection and cleaning -- Handling dates, strings, numbers -- Numerical summary and group by analysis -- Frequency distributions and cross tabulations -- Using SQL with SAS and R -- Functions, loops, arrays, macros -- Data visualization -- Data output -- Statistics for data scientists…”

Materias: “…R (Computer program language)…”

Materias: “…R (Computer program language)…”

Materias: “…R (Computer program language) Handbooks, manuals, etc…”

Materias:

“…Il décrit ensuite certaines conséquences du renforcement de l’intensité de R-D dans l’Union européenne, les niveaux de dépenses de R-D nécessaires pour que l’objectif en matière de R-D annoncé ..…”

“…Setting R&D spending targets based on R&D intensities (GERD as a share of GDP) has been a part of science and technology policy in many OECD countries for at least 35 years. …”

Materias: “…R (Computer program language)…”

Materias:

Tabla de Contenidos: “…R Programming Fundamentals: Deal with data using various modeling techniques…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- About Packt -- Contributors -- Table of Contents -- Preface -- Chapter 1: Getting Started with R and Statistics -- Introduction -- Technical requirements -- Maximum likelihood estimation -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Calculating densities, quantiles, and CDFs -- Getting ready -- How to do it... -- How it works... -- There's more... -- Creating barplots using ggplot -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- Generating random numbers from multiple distributions -- Getting ready -- How to do it... -- How it works... -- There's more... -- Complex data processing with dplyr -- Getting ready -- How to do it... -- How it works... -- There's more... -- See also -- 3D visualization with the plot3d package -- Getting ready -- How to do it... -- How it works... -- Formatting tabular data with the formattable package -- Getting ready -- How to do it... -- How it works... -- There's more... -- Simple random sampling -- Getting ready -- How to do it... -- How it works... -- Creating diagrams via the DiagrammeR package -- Getting ready -- How to do it... -- How it works... -- See also -- C++ in R via the Rcpp package -- Getting ready -- How to do it... -- How it works... -- See also -- Interactive plots with the ggplot GUI package -- Getting ready -- How to do it... -- How it works... -- There's more... -- Animations with the gganimate package -- Getting ready -- How to do it... -- How it works... -- See also -- Using R6 classes -- Getting ready -- How to do it... -- How it works... -- There's more... -- Modeling sequences with the TraMineR package -- Getting ready -- How to do it... -- How it works... -- There's more... -- Clustering sequences with the TraMineR package -- Getting ready -- How to do it…”

Tabla de Contenidos: “…Intro -- Copyright -- Table of Contents -- Preface -- Recipes -- Software and Platform Notes -- Conventions Used in This Book -- O'Reilly Safari -- How to Contact Us -- Acknowledgments -- Chapter 1. R Basics -- 1.1 Installing a Package -- Problem -- Solution -- Discussion -- 1.2 Loading a Package -- Problem -- Solution -- Discussion -- 1.3 Upgrading Packages -- Problem -- Solution -- Discussion -- 1.4 Loading a Delimited Text Data File -- Problem -- Solution -- Discussion -- See Also -- 1.5 Loading Data from an Excel File -- Problem -- Solution -- Discussion -- See Also -- 1.6 Loading Data from SPSS/SAS/Stata Files -- Problem -- Solution -- Discussion -- See Also -- 1.7 Chaining Functions Together with %&gt -- %, the Pipe Operator -- Problem -- Solution -- Discussion -- See Also -- Chapter 2. …”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Packt Upsell -- Contributors -- Table of Contents -- Preface -- Chapter 1: Getting Started with Regression -- Going back to the origin of regression -- Regression in the real world -- Understanding regression concepts -- Regression versus correlation -- Discovering different types of regression -- The R environment -- Installing R -- Using precompiled binary distribution -- Installing on Windows -- Installing on macOS -- Installing on Linux -- Installation from source code -- RStudio -- R packages for regression -- The R stats package -- The car package -- The MASS package -- The caret package -- The glmnet package -- The sgd package -- The BLR package -- The Lars package -- Summary -- Chapter 2: Basic Concepts - Simple Linear Regression -- Association between variables - covariance and correlation -- Searching linear relationships -- Least squares regression -- Creating a linear regression model -- Statistical significance test -- Exploring model results -- Diagnostic plots -- Modeling a perfect linear association -- Summary -- Chapter 3: More Than Just One Predictor - MLR -- Multiple linear regression concepts -- Building a multiple linear regression model -- Multiple linear regression with categorical predictor -- Categorical variables -- Building a model -- Gradient Descent and linear regression -- Gradient Descent -- Stochastic Gradient Descent -- The sgd package -- Linear regression with SGD -- Polynomial regression -- Summary -- Chapter 4: When the Response Falls into Two Categories - Logistic Regression -- Understanding logistic regression -- The logit model -- Generalized Linear Model -- Simple logistic regression -- Multiple logistic regression -- Customer satisfaction analysis with the multiple logistic regression -- Multiple logistic regression with categorical data…”