This function takes a data frame, a target variable and a list of ssv and produces a regression plot of each ssv against the target. The output can written as .png file into the current working directory. Also, summary statistics are provided.
igate.regressions(df, target, ssv = NULL,
outlier_removal_target = TRUE, outlier_removal_ssv = TRUE,
savePlots = FALSE, image_directory = tempdir())
Data frame to be analysed.
Target varaible to be analysed.
A vector of suspected sources of variation. These are the variables
in df
which we believe might have an influence on the target variable and
will be tested. If no list of ssv is provided, the test will be performed
on all numeric variables.
Logical. Should outliers (with respect to the target variable)
be removed from df (default: TRUE
)? Important: This only makes sense if no
prior outlier removal has been performed on df, i.e. df
still contains all
the data. Otherwise calculation for outlier threshold will be falsified.
Logical. Should outlier removal be performed for each ssv (default: TRUE
)?
Logical. If FALSE
(the default) regression plots will be output to the standard plotting
device. If TRUE
, regression plots will additionally be saved to image_directory
as png files.
Directory to which plots should be saved. This is only used if savePlots = TRUE
and
defaults to the temporary directory of the current R session, i.e. tempdir()
. To save plots to the current
working directory set savePlots = TRUE
and image_directory = getwd()
.
The regression plots of target
against each ssv
are written as
.png file into the current working directory. Also, a data frame with the following
columns is output
Causes |
The ssv that were analysed. |
outliers_removed |
How many outliers (with respect to this ssv )
have been removed before fitting the linear model? |
observations_retained |
After outlier removal was performed, how many observations were left and used to fit the model? |
regression_plot |
Logical. Was fitting the model successful? It can fail, for example, if a ssv is constant. |
r_squared |
r^2 value of model. |
Regression plots for each ssv
against target
are produced and
svaed to current working directory. Also a data frame with summary statistics is produced,
see Value for details.
# NOT RUN {
igate.regressions(iris, target = "Sepal.Length")
# }
Run the code above in your browser using DataLab