I'm majoring in SQM and your videos are all amazing, much cleaner and easier to understand than my prof's lecture. I'm taking my time to go through every single video on this channel. Thank you and a big thumbs up.
Thank you very much sir. This is so straight-forward, clutter-free from excess info and easy to understand. It would be great if somewhere you mention about some specifics like lag.max and what values should be taken and why? , etc..
Thanks sir for such a simple way to explain the concept! Please include some real data as well in next video of series which helps to understand the real world issues comfortably
Thanks for comments and suggestion! For these introductory time-series I'll still use simpler examples keeping in mind many may be doing it for the first time. But later I plan to work on more complex situations too.
Thanks a lot for your simplified explanation. Could you please help us through a lecture explaining date formatting before converting the data frames into data series?
Hi Professor Rai, thanks for your video on time series. Here I have a question on the 'ts' command. If my data is a daily one, how should i set the frequency? how can i specify the particular starting/ending date?
Good Morning professor, Please professor, 1)- if we have the Yt series (with trend). To study the stationarity of this series, we can do the following decomposition (or filtering): Yt = F(t) + Ut, such that F(t) is stationary at the turn of deterministic trend (that is, without unit root) (linear, nonlinear (Quadratical, Cubic...). And if we find the series Ut it is stationary, it implies that Yt it does not have a unit root, and the opposite is right? 2)- If a series it is Ts (Trend Stationary) at the level, it imply that this series it is I (0) and not I(1)? Best wishes
Thank you for your valuable lecture sir, I want to ask : after I load the data by ' data(AirPassenger )' and convert to AP object. but when I want to know the Header column with function ' head(AP)' why it shown = AP head(AP) [1] 112 118 132 129 121 135 #the header was not shown like your's
Thanks for the videos. I want to know how to compare two time-series data. I am a geologist, and want to compare the time series of the same variable (such as temperature) at two locations.
Sir, how to make an ordinary dataset to time-series data? I have 10 Rows with 10 variables and 29 observations. 1st row and column is year. 2nd is Agriculture Employment. 3rd is Industry Employment. 4th is Service Sector Emp. 5th is education. 6th is Life expectancy. 7th is population growth. 8th is GDP growth. 9th is Inflation rate. And 10th is Interest rate. Three dependent variable and 6 independent variables.
Hi Sir, i have monthly ts data that has 216 observations with decimals. I removed those decimals. Then when I bring it in r and try to plot it its coming different and clumsy. Further wehen I add another data series "year" in to the data file, the figure is coming as dot. So the trend is clear but the seasonal cycle of the figure is not coming, the way you have done in your slides. In the decomposition I found another error: Error in decompose(d) : time series has no or less than 2 periods Would you please suggest me what is the problem in my analysis, Do I need to install any package? Here are my r codes: d
@@bkrai hi sir, many thanks for the reply. how to capture seasonality… My data is from Dec 2001 to December 2019 and already deleted Dec 2001 data. Therefore I tried monthly, quarterly...so on... ts(d, frequency = 12, start=c(2002,1)) ts(d, frequency = 4, start=c(2002,1:3)) ts(d, frequency = 3, start=c(2002,1:4)) Its coming the same error!
If you look at before and after log transformation plots, it will show how it changes from non-stationary to a much better pattern for prediction purposes.
The data is already available with R. If you start with 1st video in the playlist, you can see how to access it: ruclips.net/p/PL34t5iLfZddt9X6Q6aq0H38gn-_JQ1RjS
I'm majoring in SQM and your videos are all amazing, much cleaner and easier to understand than my prof's lecture. I'm taking my time to go through every single video on this channel. Thank you and a big thumbs up.
Great to hear!
Thank you very much sir. This is so straight-forward, clutter-free from excess info and easy to understand. It would be great if somewhere you mention about some specifics like lag.max and what values should be taken and why? , etc..
Thanks for the feedback!
Thanks sir for such a simple way to explain the concept! Please include some real data as well in next video of series which helps to understand the real world issues comfortably
Thanks for comments and suggestion! For these introductory time-series I'll still use simpler examples keeping in mind many may be doing it for the first time. But later I plan to work on more complex situations too.
Great tutorial Sir. Very informative and nice. Thank you Sir.
Thanks for comments as always!
You're welcome @@bkrai Sir.
Great tutorial Sir. very useful for us thank you very much Sir
Thanks for comments!
sir, what is the meaning of "type" and "las" when u write the code of plotting
Thanks a lot for your simplified explanation. Could you please help us through a lecture explaining date formatting before converting the data frames into data series?
4:18 Decomposition
Thx
Thank you very much!
You're welcome!
Hi Professor Rai, thanks for your video on time series. Here I have a question on the 'ts' command. If my data is a daily one, how should i set the frequency? how can i specify the particular starting/ending date?
Good Morning professor,
Please professor,
1)- if we have the Yt series (with trend). To study the stationarity of this series, we can do the following decomposition (or filtering):
Yt = F(t) + Ut, such that F(t) is stationary at the turn of deterministic trend (that is, without unit root) (linear, nonlinear (Quadratical, Cubic...). And if we find the series Ut it is stationary, it implies that Yt it does not have a unit root, and the opposite is right?
2)- If a series it is Ts (Trend Stationary) at the level, it imply that this series it is I (0) and not I(1)?
Best wishes
Sir, can we sample from known standard probability models of time series.
Just I wanted to observe the ACVF plot for different processes.
Try and see what you get.
Then how to sample from such processes?
Pretty nice, thanks
You are welcome!
3:46 log Transformation
Thx
decomp
It got resolved when I used: decomp
Thanks for the update!
Sir , is there any video on Oracle log file analysis anomoly detaction using R and ML !
I do not have one at this time.
dataset = read.csv('airline_passengers.csv')
> class(dataset)
"data.frame"
> start(dataset)
Error in attr(x, "tsp")
If the data has a header, you may have to use header = T while reading csv file.
@@bkrai Sir thank you. I will try it
Is this split basis the additive or the multiplicative model?
It is additive.
@@bkrai is there any package in R that deals with the multiplicative model?
Thank you for your valuable lecture sir,
I want to ask :
after I load the data by ' data(AirPassenger )' and convert to AP object. but when I want to know the Header column with function ' head(AP)' why it shown =
AP head(AP)
[1] 112 118 132 129 121 135 #the header was not shown like your's
Are the next steps working correctly?
Yes, no problem. All next step is working properly. Just issue on the heading of the data
Ok, thanks for the update!
Hi Rai, very good videos really enjoying it, please can you tell where to get data to practice
This data is in R itself. You can access it by using the code that I used.
Thanks for the videos. I want to know how to compare two time-series data. I am a geologist, and want to compare the time series of the same variable (such as temperature) at two locations.
You can plot both on the same graph.
Sir, how to make an ordinary dataset to time-series data?
I have 10 Rows with 10 variables and 29 observations.
1st row and column is year.
2nd is Agriculture Employment.
3rd is Industry Employment.
4th is Service Sector Emp.
5th is education.
6th is Life expectancy.
7th is population growth.
8th is GDP growth.
9th is Inflation rate.
And 10th is Interest rate.
Three dependent variable and 6 independent variables.
For time series you need at least 2-3 years of data to capture trends and seasonality.
Hi Bhartendra, thanks for the video. One query, what if the data is daily for example COVID-19 data. What frequency we should take. Can we take 365?
Yes, try that.
Thanks. I tried that and it worked.
Hi Sir, i have monthly ts data that has 216 observations with decimals. I removed those decimals. Then when I bring it in r and try to plot it its coming different and clumsy. Further wehen I add another data series "year" in to the data file, the figure is coming as dot. So the trend is clear but the seasonal cycle of the figure is not coming, the way you have done in your slides. In the decomposition I found another error:
Error in decompose(d) : time series has no or less than 2 periods
Would you please suggest me what is the problem in my analysis, Do I need to install any package?
Here are my r codes:
d
To capture seasonality make sure you have data for 2 or more periods. Currently it detects "no or less than 2 periods".
@@bkrai hi sir, many thanks for the reply. how to capture seasonality… My data is from Dec 2001 to December 2019 and already deleted Dec 2001 data. Therefore I tried monthly, quarterly...so on...
ts(d, frequency = 12, start=c(2002,1))
ts(d, frequency = 4, start=c(2002,1:3))
ts(d, frequency = 3, start=c(2002,1:4))
Its coming the same error!
Probably you can try this:
ruclips.net/video/rV-hhKBRKbI/видео.html
Thanks sir
You are welcome!
What us the benefit of taking log?
If you look at before and after log transformation plots, it will show how it changes from non-stationary to a much better pattern for prediction purposes.
sir, am learning predictive subject.. in that am finding too much tough in Time series.. can u suggest me some links to start with time series
You can try this playlist:
ruclips.net/p/PL34t5iLfZddt9X6Q6aq0H38gn-_JQ1RjS
Pls share the R file.
Link to R file is in description area of following video:
ruclips.net/video/VQ-9BzKYVIo/видео.html
Dear Sir, Can you please give the data set & code. Thanks and regards
The data is already available with R. If you start with 1st video in the playlist, you can see how to access it:
ruclips.net/p/PL34t5iLfZddt9X6Q6aq0H38gn-_JQ1RjS
I'll try to find the code.
👌👌💐💐
Thanks!
@@bkrai सर I request you आप aspect based sentiment analysis पे video बनाओ...... Plz
I wanna be your student for R ..
How can I ?
If you are watching my videos, your are already my student :)
@@bkrai thanks so much. :)
welcome!
@@bkrai you are the most amazing person who always share his knowledge without anything.
Thanks for comments!