MatrixModels:用于稠密矩阵和稀疏矩阵建模 mvtnorm:用于计算多元正态分布和t分布的概率,分位数,随机偏差等 SparseM:用于稀疏矩阵的基本线性代数运算 lme4:利用C++矩阵库 Eigen进行线性混合效应模型的计算。 broom:将统计模型结果整理成数据框形式 caret:一个用于解决分类和回归问题的数据训练综合工具包 glmnet:通过极大惩...
model.matrix包装内stats, 底座的一部分R. 包MatrixModels中的model.Matrix;看注释'。 as(f, "sparseMatrix")(请参阅类文档sparseMatrix中的coerce(from = "factor", ..))为单个因子f生成转置稀疏模型矩阵(无对比)。
@language=N'R', @script = N'str(OutputDataSet); packagematrix <- installed.packages(); Name <- packagematrix[,1]; Version <- packagematrix[,3]; OutputDataSet <- data.frame(Name, Version);', @input_data_1 = N''WITHRESULTSETS((PackageNamenvarchar(250), PackageVersionnvarchar(max) )...
The ssgraph package offers Bayesian inference in undirected graphical models using spike-and-slab priors for multivariate continuous, discrete, and mixed data. Computationally intensive tasks of the package are using OpenMP via C++.The GPUmatrix package can offload calculations to the GPU while ...
Matrix 1.2-12 https://cran.r-project.org/web/packages/Matrix/index.html matrixcalc 1.0-3 https://cran.r-project.org/web/packages/matrixcalc/index.html MatrixModels 0.4-1 https://cran.r-project.org/web/packages/MatrixModels/index.html matrixStats 0.54.0 https://cran.r-project.org/web/packa...
data("Fishing", package = "mlogit") Fish <- mlogit.data(Fishing,shape = "wide",choice = "mode") summary(mlogit(mode ~ 0 | income, data = Fish)) 这个输出的结果与nnet包中的multinom()函数一致。由于mlogit包可以做的logit模型更多,所以这里就不在对nnet ...
forestplot(labeltext = as.matrix(rs_forest[,1:3]), #设置用于文本展示的列,此处我们用数据的前三列作为文本,在图中展示 mean = rs_forest$V4, #设置均值 lower = rs_forest$V5, #设置均值的lowlimits限 upper = rs_forest$V6, #设置均值的uplimits限 ...
在R语言中,有两个包(package)提供了LDA模型:lda和topicmodels。 lda提供了基于Gibbs采样的经典LDA、MMSB(the mixed-membership stochastic blockmodel )、RTM(Relational Topic Model)和基于VEM(variational expectation-maximization)的sLDA (supervised LDA)、RTM.。 topicmodels基于包tm,提供LDA_VEM、LDA_Gibbs、CTM_...
对于y是连续值得情况,我们可以用这种方式处理,但当y是离散值我们用普通线性模型就不合适了,这时我们引用另外一种模型 --- Generalised Linear Models 广义线性模型。 为了获取GLM模型,我们列出3个条件: ,也就是y|x为指数族分布,指数族分布形式: 如果我们判断y的假设为 ...
Matrix Sparse and Dense Matrix Classes and Methods methods Formal Methods and Classes mgcv Mixed GAM Computation Vehicle with Automatic Smoothness Estimation nlme Linear and Nonlinear Mixed Effects Models nnet Feed-Forward Neural Networks and Multinomial ...