- Видео 62
- Просмотров 184 304
Drew Tyre
США
Добавлен 3 окт 2011
Diligent professional with over 20 years of experience in data visualization, analysis, and software development within a higher education setting. Widely published with superior research and analytical skills. Excel in developing statistical models to inform decision-making
Видео
Introduction to mixed models
Просмотров 5723 года назад
Mixed models allow for observations within groups to be correlated with each other.
Introduction to cross validation
Просмотров 3633 года назад
Cross validation is a way to test model structure against independent data without holding a subset of data back.
Introduction to GAM models
Просмотров 11 тыс.3 года назад
Generalized additive models break the assumption that the relationship between y and x is linear.
AICdifferences
Просмотров 4673 года назад
The important thing about AIC scores is the differences in AIC between two or more models.
AIC intro
Просмотров 4603 года назад
A brief introduction into using Akaike's Information Criterion (AIC) for selecting between a set of predictive models.
time to event data
Просмотров 5603 года назад
Effects of censoring, proportional hazards models, survival regression, exponential distribution, weibull distribution
Carry out multiple operations to transform a data set
Просмотров 474 года назад
Previous video on basic use of dplyr data verbs: ruclips.net/video/gu8rt4JPsrs/видео.html Previous video on importing the data used: ruclips.net/video/8tnACksvayI/видео.html Download the data from: esapubs.org/archive/ecol/E084/093/
Use dplyr filter to remove rows with missing values
Просмотров 3494 года назад
Previous video on basic use of filter: ruclips.net/video/gu8rt4JPsrs/видео.html Previous video on importing the data used: ruclips.net/video/8tnACksvayI/видео.html Download the data from: esapubs.org/archive/ecol/E084/093/
Basic use of dplyr verbs select, mutate, arrange, filter
Просмотров 1094 года назад
The video on importing the data is at ruclips.net/video/8tnACksvayI/видео.html The data can be downloaded at esapubs.org/archive/ecol/E084/093/
Reading tab delimited data with read_tsv() and solving import issues
Просмотров 1,6 тыс.4 года назад
Reading tab delimited data with read_tsv() and solving import issues
estimate mean and precision from a simple random sample
Просмотров 1,3 тыс.4 года назад
estimate mean and precision from a simple random sample
Reading Problematic data with read.table()
Просмотров 2044 года назад
Reading Problematic data with read.table()
Understanding harvest and control for wildlife populations
Просмотров 6964 года назад
Understanding harvest and control for wildlife populations
Fitting the exponential model to Italy's case data and making predictions.
Просмотров 1924 года назад
Fitting the exponential model to Italy's case data and making predictions.
Make a figure of COVID-19 data for Italy.
Просмотров 1224 года назад
Make a figure of COVID-19 data for Italy.
Download and manipulate COVID-19 data in R
Просмотров 1,3 тыс.4 года назад
Download and manipulate COVID-19 data in R
Hello. I was wondering how to check the assumption that errors are independent. I believe that uve explained all the other assumptions checking with the (very clear explanation by the way, very helpful), except for the independence of the errors. Or have i misunderstood that? Thank you.
You're correct, that assumption is not checked by the graphical methods described. In general, testing that assumption is much more difficult. In many cases it's easier to verify by the logic of the sampling process used to collect the data. In the sample data I used each data point represents a single horseshoe crab. So the independence assumption means we assume that the size of one horseshoe crab is not affected by the size of another crab in the sample. That seems reasonable as long as we've collected the crabs randomly from some large population.
Amazing explanation (from an ecology student). :)
Thank you for your presentation it is very helpful! How do i add the intercept in R to get the second plot?
Excellent explanation !!
excellent explanation !!
Hello! Thank you for the video. I would like to know how did you transforme the scale of the smoothed function to the response scale in R?
See 1:45 in the video. You need to add the intercept to the function. The best way to do this is to use predict(M3) and make the plot yourself.
The video I needed to understand this. Thank you 🙏🏻
THANK YOU! I was doing some googling to try and better understand what this chart was trying to explain in R and this video is exactly what I needed.
Glad it was helpful!
Hello. I'm so confused. Why is R studio producing different results while using the same call. 😢
I'm sorry you're having difficulty with your work. There are many reasons why you might run the same code and get different results. This isn't really a great forum for fixing issues like that, unfortunately. I suggest you look for help at forum.posit.co, stackoverflow.com (search for questioned tagged 'R') or stats.stackexchange.com.
Thank you for the great explanation
Very clear and concise, thanks! Minor detail: the Greek letter at 5:00 is not 'nu', but 'eta'.
Nice
Don’t Adam and Eve it.
Good video my man
Hi there anyone know if this is meant to say '10th of a percent per "year"' as opposed to '10th of a percent per "generation"'? at 08:30
How would we interpret the parametric coefficients (if we had any) or test statistics? Same as regular glm?
Thank you for your videos! I am finding them very helpful.
can you upload fitting of this data through R package frair or any other way.. A lot of students out there are struggling to understand fitting of functional response
Wow it's all so clear now, thank you so so much ^-^
Great video. Thank you for the clear explanation!!!
Thank you for your explanation, do you have any videos related to cluster sampling and two stage sample design, as well?
Very useful! Thanks a ton for posting this ans explaining it clearly.
examples would be more helpful but its fine
what does mean population sizes? during analysis or what
Population size in this case refers to the number of individuals in a particular area. For inbreeding effects, we mean the actual number of individuals, as opposed to an estimate of population size.
Nice presentaion sir , How to get mathematical equation form of the fitted non linear data sir?
Unfortunately there isn't a simple equation form for the non-linear spline. It is a weighted sum of "basis functions" . This paper has a good exposition of the basic idea: esajournals.onlinelibrary.wiley.com/doi/abs/10.1002/ecy.1674
And that's what a log link is in GLM's :D
Is that level of Nebraska university engineers? What is that you teach your engineers? How to pass data to a library written by someone these engineers never met in their life. What they gonna do when this library will be replaces by another library? It takes 15 min to explain average student the concept of GAM and 45 min for average student to write working code. Is it the goal of American higher education to produce idiots?
Not targeted at engineers or statisticians, but scientists who haven't been taught to write code or any math beyond 1st year calculus.
This was the best explation over this topic I had. Thank you so much.
Edited: Thank you for this walk through. I just want to get your opinion on how you view the assumptions underlying regression methods. Compared to my field [applied econometrics], would you expect the assumptions to be violated to some degree as applied in ecological statistics? Is the hope of the applied [statistician] that the model is a good-enough approximation of the process that generated the observed data? How does one distinguish that good-enough threshold? Finally, does removing outliers to attain better measured deviations increase the risk of overfitting?
Quote from George Box: "all models are wrong, but some of them are useful" -- wrong in the sense that the assumptions are nearly always false to some degree. I'm not familiar with much from econometrics, but what little I do know suggests that the data sets tend to be larger than in ecology, which helps a lot. Econometric data suffer from less "observation error". Distinguishing the "good enough" threshold is a matter of judgement, and you get better with experience. One way to develop a good "eye" is to simulate data and fit the model -- the data meets the assumptions exactly and you get to see what the residuals "should" look like. As far as removing outliers goes, there are many published methods for testing for outliers. Sometimes removing a data point improves the current model, sometimes not. It's another area where experience, and subject matter knowledge, makes a big difference. Depending on "how" the outlier is removed, you may get a biased estimate as well. I would say it's an area where expert statistical help is a good idea.
Thanks alot.. you gave a real life example of how glm helped better represent the data.
Thanks! This was useful for someone like me who needs to conceptually understand GAMs rather than understand them through heavy statistical jargon. I'm curious what happens when there's more than one predictor. Does each predictor receive its own unique set of link functions or are the same link functions applied equally to each predictor?
I'm glad it was useful!! It's better to think of the link function as associated with the response, rather than the predictors. So there is only one link function for a model. The predictors are just added together on the linear scale, and the link function applies to their sum.
Very good explanation! Thank you! How to answer the "old" question of "how many samples in total"?
Neatly Explained! Thank you Drew :)
Objectively explained. Thanks.
Any chance of getting access to the code used to generate the plots used in this video? Thanks!
Ugh. Reproducibility fail! I reproduced those figures over at my blog: drewtyre.rbind.io/post/checking-assumptions/ hth.
Great explanation. Thank You.
Very helpful, thank you
Great explanation, thank you!
Clear and succinct presentation. This was helpful for me. Thanks!
nice video!
Why do you include (N-1) in the levin eq?
Hi Elly! Thank you for your question! The equation I showed uses p for the proportion of occupied patches, and the colonization term includes (1-p) because colonizations can only happen when there are empty patches. The fewer empty patches, the fewer colonizations occur. The wikipedia page for metapopulations (en.wikipedia.org/wiki/Metapopulation) uses N for the fraction of unoccupied patches, which seems a bit misleading to me. But again, the colonization term includes (1-N) for the same reason.
Thank you for the video. Is there any step by step demo of how to fit that model at the end of the video? I cant follow the part with error structure and confidence interval
Sorry, not at the moment, but I'll put it on my list of good ideas to implement.
In the meantime, maybe the week 5 lab at drewtyre.rbind.io/classes/NRES803/ will help
@@DrewTyre Thanks, looking forward to it. Just another idea: may be it is great to talk about how those link functions are derived?
This video is really helpful. Thank you for this. Love from India.
Glad it was helpful!
Please, which program did you use to do this analysis?
These are fitted in R using the function nls()
@@DrewTyre thanks!
this is a really good explanation, especially of the link function. Thank you.
Hello! I just found your channel, and I wanted to thank you for the clarity of your explanations and content! It's difficult to find lectures, especially as concise as yours. I'm so excited to watch and practice what I've been learning in my ecology classes, and I wanted you to know that your videos are appreciated. (Also, I really like your Covid-19 in R series, I'll be practicing along as soon as my finals are over) Thank you!
Glad it was helpful!
I need this version of sqlite manager but iam not getting this version .when i dwld firebox the new version of sqlite manager is showing there and i dont know how to work on that.could pls help me how can i dwnld this version....
I always wondered how big the population would have to be to prevent inbreeding, this helps me actually.
thank you that was a really nice explanation
Interesting and informative!