A dataset containing the ratings and other attributes of 187 movies.

datasets

To fit the kernel semi-parametric model and its extensions. It allows multiple kernels and unlimited interactions in the same model. Coefficients are estimated by maximizing a penalized log-likelihood; penalization terms and hyperparameters are estimated by minimizing leave-one-out error. It includes predictions with confidence/prediction intervals, statistical tests for the significance of each kernel, a procedure for variable selection and graphical tools for diagnostics and interpretation of covariate effects. Currently it is implemented for continuous dependent variables. The package is based on the paper of Liu et al. (2007), <doi:10.1111/j.1541-0420.2007.00799.x>.

Catherine Schramm

KSPM

Kernel Semi-Parametric Models

Aurelie Labbe

Celia M. T. Greenwood

csm function

A data frame with 187 rows and 13 variables:<dl class="dl-horizontal">
 <dt>Year</dt><dd>year at which movies were projected on the screens</dd>
 <dt>Ratings</dt><dd>ratings</dd>
 <dt>Genre</dt><dd>genre of the movie</dd>
 <dt>Gross</dt><dd>gross income in USD</dd>
 <dt>Budget</dt><dd>budget in USD</dd>
 <dt>Screens</dt><dd>number of screens in USA</dd>
 <dt>Sequel</dt><dd>sequel</dd>
 <dt>Sentiment</dt><dd>sentiment score</dd>
 <dt>Views</dt><dd>number of views of movie trailer on Youtube</dd>
 <dt>Likes</dt><dd>number of likes of movie trailer on Youtube</dd>
 <dt>Dislikes</dt><dd>number of dislikes of movie trailer on Youtube</dd>
 <dt>Comments</dt><dd>number of comments of movie trailer on Youtube</dd>
 <dt>Aggregate.Followers</dt><dd>aggregate actor followers on Twitter</dd></dl>

csm: Conventional and Social media features of 187 movies.

Description

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References