# Questions tagged [state-space-models]

It describes the probabilistic dependence between the latent state variable and the observed measurement.

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### Parameters in mlemodel in statsmodel

I am trying to run a TVP-VAR on statsmodel for a big data, but seems to run in a problem when I am trying to validate the vector matrix and the vector shape. Particularly, in the start and the update ...
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### How do we identify parameters in this simple model?

Consider the following model: $$y_{it}=\nu_{it}+\epsilon_{it}$$ $$\nu_{it}=\rho \nu_{it-1}+\zeta_{it}$$ Where $y_{it}$ is the income for $i$ at time $t$. $\epsilon_{it}$ is the idiosyncratic income ...
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### State space models in python statsmodels: including lag state innovation in observation equation

I am trying to fit the following state space model via the (excellent and highly useful) statsmodels state-space module. The model is a standard local level model but where last period's innovation ...
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1 vote
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### Fitting TVP-VAR statespace mlemodel in statsmodel

1 Thanks to everyone in advance for their time! I am trying to run a TVP-VAR for a panel in the statespace mlemodels in statsmodel. I get an error while trying to fit the model ...
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### Full conditional distribution (for Gibbs sampling) when model contains a logical node

I'm working on a time series model using a Bayesian implementation in JAGS. The simplest version of my model is an integrated random walk. The heart of the model is this: $y_t \sim N(\mu_t, \sigma)$ ...
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### Slice sampling in Particle Gibbs with Ancestral Sampling

Bear with me as I am not from statistical background. My question is about the implementation of PGAS algorithm as given in Lindsten et. al 2014 concerning sampling in state-space models. The two ...
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### Subspace method fails at identifying parameters in a state space system

I am trying to infer the parameters of a linear multivariate time-invariant state space system using a subspace method. However, the inferred parameters do not match the ground-truth parameters used ...
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I'm trying to fit the following model: $y_t = \left[\begin{matrix} (1-w) & 1 & w \end{matrix}\right] \left[\begin{matrix} d_t \\ \mu_t \\ m_t \end{matrix}\right] + \mathcal{N}(0,\sigma_\eta^2)... 1 vote 0 answers 156 views ### Maximum likelihood parameter estimation for state space model (Kalman Filter) it´s about a state space model that I want to run using the Kalman filter. However, certain parameters are unknown and must be estimated by the maximum likelihood method. The state space model is as ... • 41 1 vote 1 answer 180 views ### Applying outlier adjustment using student's t distribution in a state-space model I'm exploring performing outlier adjustment in a state-space model by using student's$t$distribution. The gist of the problem is formulated as follows:$\begin{align*} y_t^* &= u_t + o_t - o_{... • 61 2 votes 0 answers 79 views ### State space model to invert moving average of AR1 process whose mean temporarily jumps up once This is a follow up query of this question. Here is the problem statement: I have an AR1 process say x[t] whose mean jumps up in a given time period. ie.x[t]-\mu[t] = \phi (x[t-1] -\mu[t-1]) + \...
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Here is the problem :- We have an AR(1) process, $x[t]$, ie, $(x[t] - \mu) = \phi(x[t-1]-\mu) + \epsilon_x[t]$ where $Var(\epsilon_x[t]) = \sigma_x^2$ and $Mean(\epsilon_x[t])=0$ ie. \$x[t] = (\mu - \...