Grasp more from your process, make analytics, focus on what matters.
Grasp more from your process, make analytics, focus on what matters.
In this post we show how an integral can be computed using Monte-Carlo method and how combination with bootstrapping can increase precision. Reference Lets say we wan to integrate the cardinal sinus over the interval . Graphically it is about…
This post shows how to adjust statistical distribution on a random sampled dataset and assess precision of regressed parameters. Synthetic dataset We create a synthetic dataset by sampling random values from a Log Normal law: We also create a support…
Synthetic dataset First let’s import few packages to do the job. Now we can create a synthetic dataset to support the discussion: Pandas aggregation magic The key to make easy and flexible aggregation with pandas is to define function with…
This post shows how ODE parameters as well as initial condition can be adjusted to experimental data using Python. Adjusting ODE parameters is good topic to introduces specific methodology such as parameter normalization and sample bootstrapping.
Pollution rose is a very important tool when dealing with Air Quality Monitoring, they help to understand from which wind sectors the pollution arises and when correlating pollution roses at several locations it can be used to triangulate specific sources…
Python is a very convenient companion for function adjustment and scientific computing in general. We present in this article a simple problem where the scipy package is the sufficient toolbox to tackle an non linear adjustment problem involving a numerical…