Hello,
Our current research work involves analysis of relationships between variables based on historical data. In general, the dataset is in the form of time-series consisting of a few variables that describe given system. In other words, our data can be stored in a matrix, say X, where xij corresponds to the value of the ith variable in the particular (jth) time point. Our target goal is to distinguish between dependent/independent variables in a given system based on the data.
I'm not a statistician, unfortunately, so I'm not sure if this is the proper naming convention, i.e. dependent/independent variables with respect to the variables that are linked by causal relationships - and this is actually what we are looking for.
My first question would be if we're going to the right direction - we started with a correlation-based methods. Basic correlation analysis indicates the strength and direction of a linear relationship between given two variables. We would like to use some more advanced analysis that would be able to judge non-linear relationships. I read that this could be done using a correlation ratio. However, I have hard time finding any information that would give some guidelines about how to do it (more specifically, how to interpret the correlation ratio value with respect to a non-linear relationship between given two variables).
I will appreciate if you could recommend me any source of information about the correlation ratio and/or any other method that could be use to achieve our goal.
Thanks in advance,
Wojciech
Our current research work involves analysis of relationships between variables based on historical data. In general, the dataset is in the form of time-series consisting of a few variables that describe given system. In other words, our data can be stored in a matrix, say X, where xij corresponds to the value of the ith variable in the particular (jth) time point. Our target goal is to distinguish between dependent/independent variables in a given system based on the data.
I'm not a statistician, unfortunately, so I'm not sure if this is the proper naming convention, i.e. dependent/independent variables with respect to the variables that are linked by causal relationships - and this is actually what we are looking for.
My first question would be if we're going to the right direction - we started with a correlation-based methods. Basic correlation analysis indicates the strength and direction of a linear relationship between given two variables. We would like to use some more advanced analysis that would be able to judge non-linear relationships. I read that this could be done using a correlation ratio. However, I have hard time finding any information that would give some guidelines about how to do it (more specifically, how to interpret the correlation ratio value with respect to a non-linear relationship between given two variables).
I will appreciate if you could recommend me any source of information about the correlation ratio and/or any other method that could be use to achieve our goal.
Thanks in advance,
Wojciech