ChisqGoF

Description

Perform the chi-squared goodness-of-fit(GoF) test to tell whether or not an observed distribution differs from an expected chi-squared distribution.

Usage

hanaml.ChisqGoF(conn.context,
                       data,
                       key,
                       observed.data = NULL,
                       expected.freq = NULL)

Arguments

Value

• Comparsion between the actual counts and the expected counts : DataFrame
  structured as follows:
  - ID column, with same name and type as data's ID column
  - Observed data column, with same name as data's observed_data column, but always with type DOUBLE.
  - EXPECTED, type DOUBLE, expected count in each category.
  - RESIDUAL, type DOUBLE, the difference between the observed counts and the expected counts.

• Statistical outputs : DataFrame
  including the calculated chi-squared value, degrees of freedom and p-value, structured as follows:
  - STAT_NAME, type NVARCHAR(100), name of statistics.
  - STAT_VALUE, type DOUBLE, value of statistics.

Examples

## Not run: 
 Input DataFrame for Preprocessing:
> data
    ID  OBSERVED    P
 0   0     519.0  0.3
 1   1     364.0  0.2
 2   2     363.0  0.2
 3   3     200.0  0.1
 4   4     212.0  0.1
 5   5     193.0  0.1

 Create chisquaredfit instance:
 > res <- hanaml.ChisqGoF(conn, data)
 Expected output:
 > res[[1]]$Collect()
      ID  OBSERVED  EXPECTED  RESIDUAL
  0   0     519.0     555.3     -36.3
  1   1     364.0     370.2      -6.2
  2   2     363.0     370.2      -7.2
  3   3     200.0     185.1      14.9
  4   4     212.0     185.1      26.9
  5   5     193.0     185.1       7.9

## End(Not run)