High-frequency data, with frequencies of hours and seconds, is needed for the database. There are also frequency options that are multi-year, bimonthly, fortnightly, ten-day, and daily. With a large database, this kind of data can be handled with the E-Views package. Using the nonparametric kernel, this software can compute long-run variances that are symmetric or one-sided.
MATLAB really does best for solving computational problems in math and engineering. Especially when you have to use a lot of functions in your solving process, or if you have a nonlinear equation that must be iteratively solved. [MATLAB] can also perform things like integration and derivation on your equations that you put into it.
MATLAB is pretty easy to use. You can extend its capabilities using the programming interface. Very flexible capabilities when it comes to graphical presentation of your data (so many different kinds of options for your plotting needs). Anytime you are working with large data sets, or with matrices, MATLAB is likely to be very helpful.
The built-in search engine is not as performing as I wish it would be. However, the YouTube channel has a vast library of informative video that can help understanding the software. Also, many other software have a nice bridge into MATLAB, which makes it very versatile. Overall, the support for MATLAB is good.
Time-series data analysis is very accessible with EViews. It makes data analysis easier without requiring the writing of intricate scripts. A database frequently needs long-term computations of covariance and variance, where the errors are randomly distributed and represent a specific kind of sequence. For regression, time series analysis, and other statistical tasks, I found time series to be useful in my agribusiness research.
How MATLAB compares to its competition or similar open access tools like R (programming language) or SciLab is that it's simply more powerful and capable. It embraces a wider spectrum of possibilities for far more fields than any other environment. R, for example, is intended primarily for the area of statistical computing. SciLab, on the other hand, is a similar open access tool that falls very short in its computing capabilities. It's much slower when running larger scripts and isn't documented or supported nearly as well as MATLAB.
MATLAB helps us quickly sort through large sets of data because we keep the same script each time we run an analyzation, making it very efficient to run this whole process.
The software makes it super easy for us to create plots that we can then show to investors or clients to display our data.
We are also looking to create an app for our product, and we will not be able to do that on MATLAB, therefore creating a limiting issue and a new learning curve for a programming language.
