Introduction to scipy stats.tmin() function

The scipy.stats.tmin() function is a method from the scipy library in Python that calculates the minimum value of an array along a specified axis using the t-distribution.

Syntax

scipy.stats.tmin(a, axis=0, args=(), **kwargs)

• a: input array or object that can be converted to an array.
• axis: axis along which to operate. Default is 0.
• args: extra arguments passed to the t-distribution function.

Returns

The function returns a single value, which is the minimum value of the input array.

Example

import numpy as np
from scipy.stats import tmin

a = np.array([[10, 20, 30], [40, 50, 60], [70, 80, 90]])

print(tmin(a))  # Output: 10.0
print(tmin(a, axis=0))  # Output: [10. 20. 30.]

In the above example, we first create a 2-dimensional array a with values ranging from 10 to 90. We then use the tmin() function to calculate the minimum value of the entire array, which is 10.0. We also use the tmin() function with axis=0 to calculate the minimum value along each column, which is [10. 20. 30.].

Additional Notes

• The scipy.stats.tmin() function uses the t-distribution to calculate the minimum value of an array. This can be useful when dealing with small sample sizes and unknown population variances.
• The scipy.stats.tmin() function can be used in conjunction with other functions from the scipy.stats module, such as tmean() and tstd(), to perform statistical analysis on arrays.