After a long search, I finally found the explanation I was looking for. You break down complex concepts really well, keep it up, I am sure your channel will grow exponentially.
Thank you for this, man. I somehow ended up in an advanced geostatistics class as a complete newbie and so far I've just been following the instructions without even understanding what's going on. You present these matters in a way that is super easy to follow, irregardless of the persons background. :)
Thank you for such a clear and concise explanation of kriging! I have been struggling a bit to understand the 'why' of kriging and how to interpret my data- following labs like a cookbook and just 'getting through them' will not help me with a GIS career, so I appreciate you so much!! Subscribed! I will look for more videos, thank you again!!!
Very well done! When you say, this formula, what it means in English ..., this is exactly the missing part from so many people trying to pass the same message, this is why most of them fail I think. Bringing math to everyone's real life. This is how we recognise Masters as well. Big thank you.
Awesome video. This guy has all the potential to become a great teacher. This would be nice if you can make a video on different types of kriging models, and how to implement them on a GIS framework :)
I started my research reading recently and was feeling struggled with understanding the definition and formula. This video gives me a brief and clear intro to Spatial Stat. It helps me a lot! LOL
Thank you very much for this video! :) It's the best explanation I've seen so far. I'd like to hear more about the math behind the Kriging model. It would be also interesting to hear more about other applications, e.g. engineering application of the surrogate (Kriging) model.
WOW EVERYTHING IS MAKING SO MUCH MORE SENSE NOW!!! Thank you so much, your videos are saving me rn. I would love to see more spatial statistics content if you ever were thinking about it!! Wow though, thank you a thousand times.
Wow this video is a lifesaver.. Thank you so much.. This is what you call a crystal clear explanation. Please go ahead with the mathematical concepts behind this as well. Thank you very much again.
Thank you for this video. It’s very clear. Gamma of h is more precisely the expected value of the squared differences between all pairs of point a distance h apart. Although to discuss the intuition behind it you can consider a single pair of points as you have done.
man, that was the most indispensable video lacking on RU-vid in the area of data science. wish the younger me were able to watch this video instead of sifting through the papers about kriging. thanks aplenty!
This is a really good video. I was able to understand and I'm not even a statistics or mathematics student. I'm studying Geographic Information Systems and Kriging is one of the most common Spatial Interpolation methods.
Man your explanation is so clear :D you did a great job, hopefully you can make another video about krigging model like ordinary, simple, etc.. you really inspiring me :)
Excellent explanation, thank you! This is how all mathematical topics should be explained in my opinion. Bad communication in math is like bad communication in software development, sure you can write all the thousands of lines of code in one line, the compiler will understand it! But this is not optimal if you're trying to convey an idea to others.
Good job. Would like to see more detailed mathematics behind. This seems like combo of multiple linear regression fitting with KNN regression algo. Not in details but in approach and logic behind algo. I definately need more maths to fully grasp this. Thanks anyway. Keep up a good work.
Great video, easy to digest, and as an on-going bachelor in earth science, i really recommend this for you whom have absolutely zero idea about kriging model (imma recommend this too for my colleagues lol). However, one question. At timemark 9:56 - 10:10, the matrice equation includes matrice b which has the semi-variogram calculation between Xnew and Xi. The calculation itself supposed to knew Ynew, right (as showed in the video)? But Ynew is our main objective, which is unknown...bit entangled on this one.
I have exactly the same question. This is why I was going through the comments. Thank you. Perhaps the answer is given in another video. We can still solve the equation, but with 5 + 1 = 6 unknown variables (w1, w2, w3, w4, w5, Ynew) instead of w1, w2, w3, w4, w5.
Really clear video about the topic, thank you very much. I would love to see video explanation of the math being the kriging model, if it is explained as well as this video. Thank you!
Hi Ritvik I loved this video and it really saved me a lot of time, I literally could not have found a better explanation. You mention in this video that you can make a separate video for the mathematical part, can you please do that or let me know if you have already made a video. Thanks!
Goog job. I liked the video since i have been looking for videos in this topic for too long. I hope u can go ahead for the mathematical explanation. I would love it if you could help and make introduction about the Expected Improvements that is used along with kriging model to increase the fidelity of the model. Thanks alot
