math23c_bot()

Usage

math23c_bot(data=NULL, t=5, bar=FALSE, dist=FALSE, perm=FALSE, table=FALSE,
            scatter=FALSE, ctree=FALSE, neuralnet=FALSE, col1=NULL, col2=NULL,
            val1=NULL, val2=NULL, N=10^4, limit=7, color=NULL, shape=NULL,
            size=NULL, log=FALSE, myf=NULL, variable=NULL, outputs=NULL,
            outIn=NULL, hidden=1, string=NULL, err="sse", lin=FALSE,
            modelMatrix=NULL)

Arguments

data - Provide the function with your dataset csv file. If left blank, the function will prompt you to select the file in your folder.

t - The “time” between each step. Not necessarily 1:1 with seconds.

bar - Set as TRUE if you want barplots of your data.

dist - Set as TRUE if you want to test the fitting of a gamma and normal distribution to every column in your data.

perm - Set as TRUE if you want to do a permutation test involving two columns of data.

table - Set as TRUE if you want contingency tables of your data.

scatter - Set as TRUE if you want to see a scatterplot between every two columns in your dataset, in both orders.

ctree - Set as TRUE if you want to make a prediction using a decision tree.

neuralnet - Set as TRUE if you want to make a prediction using a neural net.

col1 - The first data column used in the permutation test.

col2 - The second data column used in the permutation test.

val1 - The value in col1 you want to test. Can also be c().

val2 - If left blank, the permutation test is done using val1 vs. everything that isn’t val1. If val2 is given, the test is done in terms of val1 vs val2. Like val1, this value can actually be several values using c().

N - The number of iterations used in the sampling for the permutation test.

limit - This integer value limits the function to creating contingency tables using data columns with only a certain number of unique values. Useful for avoiding the creation of gigantic unreadable contingency tables.

color - The color parameter used in ggplot.

shape - The shape parameter used in ggplot.

size - The size parameter used in ggplot.

log - If TRUE, scatterplots will use logarithmic regression instead of linear regression.

myf - The myf parameter used in ctree().

variable - The (string) name of the variable to be used in the decision tree.

outputs - The data column representing the outputs of the neural net will be split into n columns, with n being the number of discrete values in that column. The integers denoting the positions of these new columns in the resulting pre-processed dataset go into a c() for this argument. For example, if the output is the first dataset column and contains 9 discrete values, use c(1,2,3,4,5,6,7,8,9).

outIn - The formula parameter in neuralnet().

hidden - The hidden parameter in neuralnet().

string - If the output column has discrete integer values, these must be converted to strings. This parameter takes in an integer representing the position of the column in the dataset.

err - The err.fct parameter in neuralnet().

lin - The linear.output parameter in neuralnet().

modelMatrix - The object parameter in model.matrix(). For this parameter, use as.formula(~x+0+y₁+y₂+…+y_n) where x is the name of the output column, and y₁…y_n are the names of the input columns