I like the part that explains the nugget with three different plots. of course the other part of the video is also very clear and in very logical order to help us understand what variogram is including how to calculate though R is able to do it, but with the understanding on the mechanism, one can apply it easily instead of forgetting it all days later after the lecture. well done!
Sir, these lectures really helped me to comprehend the functionality of variogram modeling. Although I took this course at university before, after watching these lectures I got better understanding of statistics and geostatistic. Thank you so much for these resources. I assure you these lectures are so valuable. Kind Regards.
At observation 3 we r talking about a variance which is sill and value is 1. Is is the variance value of Semivariogram values (values of Gamma, plotted in Y axis)?
I think that the variogram should look heteroskedastic with larger lag distances having a fuller collection of similar and dissimilar values... especially when studying fragmented landscapes.
Very interesting and helpful video. Thank you very much. I have question, how can we choose the lag distance for our data? What are the things we need to consider on choosing lag distance? Thank you for your time.
Sir, Could you provide more explanation of c=variance-variogram and its derivation. It would be highly appreciated. Nicely explained . Very informative video.
The sill and the variance are not the same (Barnes, 1991) You say several times that the sill is the sample variance but that is only true for the population variance. Given the sample variance and a sample of finite size it will not be the same. Particularly if the sample has a slight trend (if the mean is not constant), but also if it is indeed constant.
Howdy Frederik, Good comments. I agree that the use of the sample variance as the sill is a practical approach that implies inference with respect to the population that we attempt to model with estimation or simulation. Also, given the assumption of stationarity we need to model the trend, remove and work with the stationary residual. There are many details that I cannot cover in an introductory course. Thank you, Michael
thank U very much. I really understand about your video. Can you give me facebook or how can i contact with you? I still didn't understand why in semivariogram function has 1/2 :(
Awesome!! There cannot be any better explanation than this.
Thanx! I'm stoked about folks benefiting from the content.
Your lectures about spatial interpolation and prediction are really useful. Thanks for spending time in producing this work to the geostat community.
I like the part that explains the nugget with three different plots. of course the other part of the video is also very clear and in very logical order to help us understand what variogram is including how to calculate though R is able to do it, but with the understanding on the mechanism, one can apply it easily instead of forgetting it all days later after the lecture. well done!
1:10 Measuring spatial continuity
8:15 Variogram observation
20:45 Spatial variability
Crisp and Informative, much appreciated!
Would like to see more spatial statistics playlists in the future, Thanks!
i understand from u much more than reading lots of famous books . u r just amazing 👍👍
Thats amazing explanation about variograms. Really thanks for investing your time to produce so quality content !
I have looked for geostatistics and your videos are incredibly helpful, Thanks a lot.
My pleasure. Glad to hear it!
Incredible introduction to variograms - Thank you for this video!
Best I could find on an introduction to variograms!
pro trick: watch series at flixzone. Me and my gf have been using them for watching lots of of movies lately.
@Jermaine Baker definitely, have been watching on Flixzone for since december myself :D
@Jermaine Baker Yea, I've been using flixzone for months myself :D
You made me fall in love with geostatistics again.
Great video. Adds are turned on though for this one, which is a shame.
Great explanation! The last slide was really helpful to understand better variance/continuity
What can be the physical interpretation of negative correlation? How is it possible that places dislike each other?, Michał Michalak
This guy is a Hero
Thank you Tunc! I'm stoked to hear that my lectures are helpful! All the best, Michael
Sir, these lectures really helped me to comprehend the functionality of variogram modeling. Although I took this course at university before, after watching these lectures I got better understanding of statistics and geostatistic.
Thank you so much for these resources. I assure you these lectures are so valuable.
Kind Regards.
At observation 3 we r talking about a variance which is sill and value is 1. Is is the variance value of Semivariogram values (values of Gamma, plotted in Y axis)?
Great Lecture Prof.
Is there a conventional way to test for proportional effect in your variogram ?
Thanks a lot, for making these videos. Can I get this ppt?
Clearly explained! Thanks a lot.
So can we say that nugget is a low pass filter i.e. it removes short-scale features?
Thank you for sharing this series of lectures
I think that the variogram should look heteroskedastic with larger lag distances having a fuller collection of similar and dissimilar values... especially when studying fragmented landscapes.
Thank you so much, شكرا جزيلا
Thank you so much great explanation
Thank you so much, it's much easier to study my theory notes now!
I'm stoked to hear that my content is helpful! Thank you for letting me know.
Very interesting and helpful video. Thank you very much.
I have question, how can we choose the lag distance for our data? What are the things we need to consider on choosing lag distance? Thank you for your time.
Great explanation! Thank you for this video
Thank you Very much!!!
Sir, Could you provide more explanation of c=variance-variogram and its derivation. It would be highly appreciated. Nicely explained . Very informative video.
Simply amazing
Thank you Nwankwo! I hope my content is helpful.
Extremely helpful Prof. I will be visiting your channel regularly henceforth.
The sill and the variance are not the same (Barnes, 1991)
You say several times that the sill is the sample variance but that is only true for the population variance. Given the sample variance and a sample of finite size it will not be the same. Particularly if the sample has a slight trend (if the mean is not constant), but also if it is indeed constant.
Howdy Frederik, Good comments. I agree that the use of the sample variance as the sill is a practical approach that implies inference with respect to the population that we attempt to model with estimation or simulation. Also, given the assumption of stationarity we need to model the trend, remove and work with the stationary residual. There are many details that I cannot cover in an introductory course. Thank you, Michael
@@GeostatsGuyLectures Thank you for the response Michael
THANK you sir ❤️
súper excelent! love it!
thank you. thank you!!!!
Thank you bro.
great
Helpful, need your tweeter account
@GeostatsGuy
thank U very much. I really understand about your video. Can you give me facebook or how can i contact with you? I still didn't understand why in semivariogram function has 1/2 :(