simonmolinsky / pyinterpolate-paper Goto Github PK

Hi @szymon-datalions

Thank you for your excellent work.
I am a little confused about the Poisson Kriging System in your code.

There is an error term m*/n(vi). m*: population-weighted mean of the N rates and n(vi): the size of population at risk.
I am not sure how you program it in your code.
Thank you for your time and any possible responses.

I must create better descriptions / graphs of use cases.

Questions:

• Why is it interesting and why should I use this software?
• When it's not a good idea to use this package?
• What data sources do I need?
• How to use defined Kriging systems? (Step-by-step with clear explanations).

• test Ordinary and Simple Kriging of points (probably existing dataset),
• test Centroid-based Poisson Kriging, ATA and ATP Kriging, compare results to the simple models (Ordinary Kriging), check smoothing effects based on the Hot-Spot and Cold-Spot analysis, everything on prepared dataset (simulated and real-world example).

Hi @szymon-datalions

Thank you for reading the message.
I am little confused that how you get the population centroid data based on 2010 U.S. census block level data. Thank you for your help.
Many thx:)

Hi, @szymon-datalions

Thank you for reading my message.
I am just a little confused that it looks like that you did Figure5: Breast cancer population at risk map in Northeastern United States and then transformed it to get Figure 6: Area-to-Point kriging breast cancer incidence rate map. May I ask that what population size you used to calculate the rate?