Data Sampling¶

Sampling with replacement from a matrix or dataframe¶

There are two ways to sample with replacement from a matrix or dataframe:

The sampleData() procedure.
The rndi() procedure.

The sampleData() procedure directly returns a sample from a matrix or dataframe. The final argument is an indicator for replacement and should be set to 1 to indicate sampling with replacement.

Example: Sampling with replacement from a matrix¶

// Set seed for repeatable random draws
rndseed  23423;

// Create a 7x2 vector
x  = { 1.2 1.8,
       2.7 2.1,
       3.0 3.3,
       4.8 4.1,
       5.1 5.4,
       6.0 2.8,
       7.2 3.9 };

replace = 1;

// Take a sample of 5 rows of 'x' with replacement
sample = sampleData(x, 5, replace);

After the code above, sample is equal to:

Repeated observations of 3.0 and 3.3 occur because the sampling takes place with replacement.

The rndi() function returns random integers from a uniform distribution with the option to specify a range. These can be used as indices for sampling, enabling you to easily draw corresponding rows from two or more variables.

Note

Sampling with random indices maintains the metadata from the original dataframe and will contain variable names, types, etc.

Example: Sampling with replacement from multiple matrices¶

// Set seed for repeatable random draws
rndseed  73725;

y = { 9.1,
      2.3,
      6.7,
      4.4,
      5.1 };

X = { 8.3 8.2,
      8.8 7.9,
      2.4 1.9,
      3.9 4.2,
      8.2 9.1 };


// Create a random sample of
// integers from 1 to 5
idx = rndi(5, 1, 1|5);

// Use 'idx' to draw corresponding rows from 'y' and 'X'
y_s = y[idx];
X_s = X[idx,.];

After the code above:

idx = 5    y_s = 5.1    X_s = 8.2    9.1
        4.4          3.9    4.2
        2.3          8.8    7.9
        6.7          2.4    1.9
        5.1          8.2    9.1

Example: Generating indices to sample from a matrix¶

// Load data from the 'fueleconomy' dataset
// in the GAUSS examples directory
file_name = getGAUSSHome("examples/fueleconomy.dat");
fueleconomy = loadd(file_name);

// Create a 100x1 vector of random
// integers between 1 and 100
range_start = 1;
range_end = rows(fueleconomy);
idx = rndi(100, 1, range_start | range_end);

// Draw a 100 observation sample from 'fueleconomy'
fuel_sample = fueleconomy[idx, .];

Sampling without replacement from a matrix¶

The sampleData() procedure can also be used to sample from a matrix or dataframe without replaced. In this case, the final argument should be set to 0 to indicate sampling without replacement.

Example: Sampling without replacement¶

// Set seed for repeatable random draws
rndseed  23423;

// Create a 7x1 vector
x  = { 1,
       2,
       3,
       4,
       5,
       6,
       7 };

// Take a sample of 3 elements without replacement
s  = sampleData(x, 3);

Note

Setting the rndseed() before using sampleData() should be done if you want to replicate the same sample each draw.

Drawing a random sample from a dataset¶

The exctSmpl() procedure draws a sample with replacement from an existing data file and saves the result as a new data file. Neither the data file drawn from nor the new sample created are saved in the GAUSS workspace.

The exctSmpl() procedure returns the number of rows in the new data file OR an error code. Specific error code details are available in Command Reference listing for exctSmpl().

Example: Sample from data file¶

// Create file name with full path
fname = getGAUSSHome("examples/credit.dat");

// Randomly sample 30% of the rows from 'credit.dat'
// and write them to a new dataset in the
// GAUSS working directory, named 'sample.dat'
n_rows = exctsmpl(fname, "sample.dat", 30);

After the code above,

n_rows = 120

Data Exploration

Data Smoothing