Kalman Filter analysis

  • Status: Pending
  • Hadiah: $150
  • Penyertaan diterima: 1

Ringkasan Peraduan

I would like use the Kalman filter (not smoother) to estimate smooth values - in real-time - (for the position (Pt) and "velocity" (Vt, first derivative) of the attached time series.

This time series shows clear signs of mean reversion around zero, meaning that the acceleration (At, second derivative) should have a negative coefficient with Pt.

I would prefer a R-based solution, preferably using the FKF package.

I tried the following transition equation, unsuccessfully.

P(t+1)=(1 1 0.5 ) P(t) + Noise(P)
V(t+1)=(0 1 1 ) V(t) + Noise(V)
A(t+1)=(-Z 0 1) A(t) + Noise(A)

Additionally, I would like noises to be estimated (and not inputted).

As a newbie in Kalman filter, I’ve been struggling with this, but for someone who’s familiar with R and the Kalman filter, it should be an easy task.

Kemahiran Disyorkan

Penyertaan teratas dari peraduan ini

Lihat Lagi Entri

Papan Penjelasan Umum

  • freelanmohan7
    freelanmohan7
    • 4 tahun yang lalu

    Hi, Expert in Kalman Filtering here. I need few clarifications regarding this project. You have three state variables in your model and the attached file has info about only one state. What does the data represent? acceleration or position? What is Z in those equations. I guess the information you provided is incomplete.

    • 4 tahun yang lalu

Bagaimana mula dengan peraduan

  • Paparkan peraduan anda

    Paparkan Peraduan Anda Cepat dan mudah

  • Dapatkan berjuta penyertaan

    Dapatkan Bertan-tan Penyertaan Dari serata dunia

  • Anugerahkan penyertaan terbaik

    Anugerahkan penyertaan terbaik Muat turun fail-fail - Mudah!

Paparkan Peraduan Sekarang atau Sertai kami Hari Ini!