Linear Regression Analysis of Title Word Count and Article Time Cited using R
نویسندگان
چکیده
منابع مشابه
Using R for Linear Regression
In the following handout words and symbols in bold are R functions and words and symbols in italics are entries supplied by the user; underlined words and symbols are optional entries (all current as of version R-2.4.1). Sample texts from an R session are highlighted with gray shading. Suppose we prepare a calibration curve using four external standards and a reference, obtaining the data shown...
متن کاملArticle Title Article Title Pattern analysis using fuzzy VIKOR in locating educational facilities district Case Study: District 14 of Tehran Metropolis
With the increasing population in cities, particularly big cities, demand for public goods and services increased too. But, due to certain political-economic structure of the country, often the rates of supplies growth have been less than the demands’. The high-demand applications such as educational, for many reasons including, Lack of cities’ coordination executive bodies, financial problems ...
متن کاملRegression Models for Count Data in R
The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of these methods, a new implementation of hurdle and zero-inflated regression models in the functions ...
متن کاملtscount: An R Package for Analysis of Count Time Series Following Generalized Linear Models
The R package tscount provides likelihood-based estimation methods for analysis and modelling of count time series following generalized linear models. This is a flexible class of models which can describe serial correlation in a parsimonious way. The conditional mean of the process is linked to its past values, to past observations and to potential covariate effects. The package allows for mod...
متن کاملEstimation of Count Data using Bivariate Negative Binomial Regression Models
Abstract Negative binomial regression model (NBR) is a popular approach for modeling overdispersed count data with covariates. Several parameterizations have been performed for NBR, and the two well-known models, negative binomial-1 regression model (NBR-1) and negative binomial-2 regression model (NBR-2), have been applied. Another parameterization of NBR is negative binomial-P regression mode...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Scientometric Research
سال: 2017
ISSN: 2321-6654,2321-6654
DOI: 10.5530/jscires.6.1.3