I want to visualize several variables of discrete and continous data in one Plot.
Does anybody have suggestions for visualization examples or where I should have a look?
Thank you in advance.
You might want to check out the vtree R package https://nbarrowman.github.io/vtree
Related
I am trying to get a scatterplot like the one seen below in matlab: But I absolutely cannot get any matlab scatterplot techniques to collaborate with me in the slighest.
I have used my data to create boxplots with no issue, so suppose there is something wrong with my plotting approach.
My code currently looks like this:
Data = readtable("Dataset.xlsx"); gscatter(Data.Var1,Data.Var2)
Anyone got any guides or code advice that can help me create the intended plot?
Thanks ahead.
I would like to ask you if there is any automated method for calculating the order of ARIMA(p,d,q) model for any type of a time series data, in MATLAB.
This will make the forecasting model more accurate and will also save me some time. I would appreciate if anybody could help me.
I'm not sure if that's what you are looking for, but maybe this post on Matlab File Exchange?
http://www.mathworks.com/matlabcentral/fileexchange/25611-arfima-simulations
Could anyone please help in providing an example showing how ANCOVA (analysis of covariance) can be done in scipy/statsmodel, with python?
I am not sure if I am asking too much, but a quick search showed me this which is not informative enough for me.
Thanks!
Statsmodels uses the linear model, OLS, to estimate ANOVA. So, having additional continuous regressors as in ANCOVA does not change the analysis.
Here are a few links to the relevant documentation
Anova helper functions and examples for ANCOVA interactions
http://statsmodels.sourceforge.net/devel/examples/generated/example_interactions.html
using formulas to create the design matrix
http://statsmodels.sourceforge.net/devel/example_formulas.html
the core OLS model
http://statsmodels.sourceforge.net/devel/generated/statsmodels.regression.linear_model.OLS.html
I have managed to estimate an 'idpoly' m for my time series Z(1,:) using the 'arx' command in Matlab. Unfortunately I do not know how to use this model m for anything else.
How do I know input a second series Z(2,:) into the model to see how well it predicts on the validation data?
Thanks
Use lsim to simulate your idpoly with an arbitrary time input.
Arnaud
I am a new learner about sensors. I have no knowledge about this sensors. However I have done some sensor module which contains with accelerometer,gyroscope and magnetometer. All of them have 3 axis data (X,Y,Z).Now i have data as a TXT file format but I couldn't find any solution for extraction this data features. I am going to use this data with NNet. Could anyone help me with making program in Matlab,please? Any suggestion and opinion will be useful for me.
Thanks in advance!
As zellus suggested, the reading from textfile is well documented in MATLAB. Look for functions textread or csvread.
As I understand it, you are looking for help understanding the data that you have collected. You may get some answers here, but you are most likely better off asking what you should be looking for in a physics/engineering related forum, then coming back here for help implementing your code if need be.
As a starting point, you could try:
Plotting the change in the data over time, for each direction.
Looking at the magnitude of each of accelerometer, gyroscope and magnetometer data (using norm), and plotting these over time
Making a scatter plot of the norms of, for example, acceleration vs magnetometer - is there any correlation?
Likewise a scatter plot of X acceleration vs Y acceleration, or X vs Z etc.
Remember, in MATLAB, the plotting tools are your friend.