Modern Applied Statistics with S

By William N. Venables, B. D. Ripley. 2010

15,861 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Statistics and Probability

Citations in the corpus

Visualizing the effects of predictor variables in black box supervised learning models (2016, methodology): “For the neural network, we used the nnet package of R (Venables and Ripley (2002)) with ten nodes in the single hidden layer, a linear output activation function, and a decay/regularization parameter of 0 .”
Peeking Inside the Black Box: Visualizing Statistical Learning With Plots of Individual Conditional Expectation (2013, methodology): “iates are physicochemical metrics that are commonly collected for wine quality control such as citric acid content, sulphates, etc. The model is t with a neural network (NN) using the R package nnet (Venables and Ripley, 2002). We t a NN with 3 hidden units and a small parameter value for weight dec”
BART: Bayesian Additive Regression Trees (2008, methodology): “…Lasso) (Efron, Hastie, Johnstone & Tibshirani 2004) and three black-box models: gradient boosting (Friedman (2001), implemented as gbm in R by Ridgeway (2004)), random forests (Breiman 2001), and neural networks with one layer of hidden units, (implemented as nnet in R by Venables & Ripley (2002)).”
Addressing Age-Related Bias in Sentiment Analysis (2018, methodology): “We test the sentiment tools for age-related bias by examining the sentiment output scores using multinomial log-linear regressions (via the R package nnet [73]).”
Detecting Common Method Bias: Performance of the Harman's Single-Factor Test (2019, methodology): “The mvrnorm function of the MASS package (Venables & Ripley, 2002, v. 7.3-45) was used for data generation.”
MatchIt: Nonparametric Preprocessing for Parametric Causal Inference (2011, methodology): “Generalized linear distance measures are implemented via the stats package ( Venables and Ripley 2002 ).”
Pollination by wild bees yields larger strawberries than pollination by honey bees (2019, methodology): “We used GLMs in the r package MASS (Venables & Ripley, 2002) to (a) test the assumption that all flowers had similar amounts of autogamous pollen prior to visit sequences, (b) compare pollen deposition and strawberry mass among hand- supplemented, bagged and open control flowers, (c) test the effect”
Various Versatile Variances: An Object-Oriented Implementation of Clustered Covariances in R (2020, methodology): “2008), ‘mlogit’ from mlogit (Croissant 2019), and ‘polr’ and ‘rlm’ from MASS (Venables and Ripley 2002).”
The VGAM Package for Categorical Data Analysis (2010, background): “org/) there is polr() (in MASS; Venables and Ripley 2002) for a proportional odds model and multinom() (in nnet; Venables and Ripley 2002) for the multinomial logit model.”