I am working on statistical analysis of my time series wind data. My data consists of two columns, first column is ‘wind speed’ in meters/sec and second column is ‘wind direction’ (0 -360 degrees). The length of the data is nearly 30 years with 1 hour frequency. Which means number of samples/rows in my data are 30years*365days*24hours=262,800 samples. This sample number may change due to leap years.
The aim of this project is to calculate the extreme values for various return period intervals, example; 1, 10, 50 and 100 year periods. This program should preferably use Numpy and/or Scipy which are commonly used libraries.
The detailed explained along with sample figures of expected outcome is provided in the attached document.
I can provide with the sample data set to work with the code and few reference documents. Please message me for any further clarifications.
Important Note: The explanation given for methodology is only a broad understanding, it is the bidders responsibility to follow/choose correct methods and techniques.
Additionally we need future assistance with any identified bugs or errors in the code.
Skills required for this project: Python (Numpy and Scipy) and Statistics (probability density functions, probability of exceedance, probability of joint occurrence)
16 freelancers are bidding on average ₹10448 for this job
I have a master's in statistics. I am quite knowledgeable about time series modelling like arima, prophet, tbats etc. I have 2 years of experience coding with python. I will complete the job within the deadline.
Hi, I recently completed my MsC thesis on time series analysis of multi-dimensional data. Your project seems to allign well with my expertise. Additionally, we could predict these extreme values.