Tagged Questions
0
votes
0answers
42 views
When to use the raw dataset as opposed to a transformed dataset for computing divergence?
Let us assume I have a set of observations:
Dataset 1: Raw
$A = [a_1,a_2,a_3,a_4,...]$
$B = [b_1,b_2,b_3,b_4,...]$
One assumptions before I proceed: Range of the values that the random variable ...
2
votes
0answers
45 views
Reasoning about an arbitrary transformation function based on observed data
I have two lots of data that have been independently, arbitrarily transformed from the same original data source using the same permutation algorithm. I would like to know what kind of statements I ...
3
votes
0answers
164 views
Normalization/comparison-when the observed cardinality is a random variable, over finite sets
Given, $p_{ij}=\frac{|A_i|+|A_j|}{|A_i\cup A_j|}$ for sets $A_i$,$A_j$ $\forall i\not=j ,\forall i \in \left \{ 1,2...n \right \} $ and given the fact that $|A_i \cap A_j|>0$ for all $A_i,A_j$: ...
3
votes
0answers
142 views
Methodology for validation of stochastic simulations with Kolmogorov-Smirnov test
I'm a phd student in Geography, i need some help (or good ressources) to understand why and when i need to use PIT (Probability integral transform) in my validation program for simulation.
I explain ...
1
vote
0answers
102 views
Is it valid to model discrete numerical test scores as coming from a continuous random variable?
I'm working with a sample of test scores which range from 0 to 100. These scores are generated from a set of 100 binary responses (0 or 1), so the higher the resulting sum, the better the performance. ...
