This video extends the probability transformation rule from the
scalar case to the vector case for vector functions of random vectors.
The video discusses how the Jacobian determinant needs to be calculated
instead of a simple gradient, and therefore this can influence whether
the Jacobian or its inverse should be calculated depending on the ease
of calculating the derivatives for the mapping or inverse mapping. The
video provides a reminder of the physical interpretation of the
Jacobian. Finally, the video considers the probability transformation
for the Polar to Cartesian coordinate mappings.
PGEE11164 Probability, Estimation Theory, and Random Signals Lectures -- School of Engineering, University of Edinburgh. Copyright James R. Hopgood and University of Edinburgh, Scotland, United Kingdom (UK). 2020.
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