Hidden Markov Models are used for modelling systems that are assumed to be Markov processes with hidden (i.e. unobserved) states.

learn more… | top users | synonyms (1)

0
votes
0answers
4 views

difference between forward backward, alpha beta, sum product, baum welsh

For Hidden Markov Models, what the difference between forward backward, alpha beta, sum product, baum welsh?
2
votes
0answers
32 views

How is prior knowledge of letter/word patterns incorporated into handwriting (or speech) recognition?

Using handwriting recognition as an example, we can train various models to recognise individual characters but to actually be useful we must incorporate prior knowledge of common character sequences, ...
0
votes
0answers
8 views

How to reestimate GMMs in a HMM-GMM

Context: Automatic Speech Recognition I understand the training of a pure HMM with Baum-Welch: Expectation step compute $\gamma_t(i) = P(q_t=i |O,\lambda)$ //p(passing state $i$ at frame ...
1
vote
0answers
11 views

How can I train HMM for continuous sign language recognition?

Currently I can recognize isolated words using HMM (Hidden Markov Model) through training an HMM model for each sign, and for a new word I take the sign for the model giving the highest likelihood. ...
0
votes
0answers
14 views

How is $\sum\limits_{t=1}^{T-1} \xi_t(i,j)$ the expected number of transitions in Baum Welch

Context: Baum-Welch Algorithm, Maximization step Serveral tutorials, e.g. this one say that $\sum\limits_{t=1}^{T-1} \xi_t(i,j)=\sum\limits_{t=1}^{T-1}\frac{P(q_t=i, O | \lambda)}{P(O|\lambda)}$ can ...
0
votes
0answers
28 views

hmmtrain default prior vector

I am using hmmtrain as follow: [trans,emiss]=hmmtrain(symbol_seq,trans0,emiss0); My question is: What is the default prior vector (pi) that used in hmmtrain.m ...
0
votes
0answers
22 views

Sensitivity to scaling of multivariate data with HMM

I have some multivariate data, say 40 features. Some features are scaled between 0 and 1, and some are scaled between 0 and 1e8. For reference, I am using sci-kit learn's HMM implementation (yes, I ...
1
vote
0answers
23 views

Connection between Hidden Markov models and logistic regression?

This question is inspired by a comment below this question on Hidden Markov models: "Have you considered logistic regression? For non longitudinal data, they are practically the same thing." My ...
0
votes
0answers
6 views

Material on plate notation of bayesian hidden markov model

Does any one know some materials on plate notation of Bayesian Hidden Markov Model? Say, given multiple observed sequences, how to infer the posterior distribution of the parameters, and the ...
0
votes
0answers
15 views

hmm variable number states

I have looked around for a while but cant seem to find any literature on this but can't seem to find a treatment. I have a set A of observations at time $t_n$ $A = \{A_1... A_n\}$ Further I know that ...
0
votes
0answers
12 views

Ttests for DNA sequences

Let's say I have two sets(1000 sequences in each set: set1 and set2) of independent DNA sequences of length 30. I created a HMM model by using DNA sequences in set1 which calculate Prob(Seq/Model). It ...
0
votes
0answers
16 views

Impulse Response Analysis for Markov-Switching Models

I've estimated a bivariate Markov-Switching VAR(1). I am interesting in understanding how an error/ 'shock' would propagate through the system. I've been stuck on how this could be done? Thank you!
2
votes
0answers
33 views

Markov models that with several active states

Are there any Markov-like models that can have several active states? So say if trying to determine (the chance) when the person will wake up based on two variables (weather and the time the person ...
0
votes
0answers
38 views

How to choose between VOMs and Predictive models, e.g., ARIMA?

In time series prediction, there is a lot of work that uses predictive models (e.g., ARIMA). On the other hand, there's also a lot of work that uses Variable Order Markov models (e.g., context ...
0
votes
0answers
25 views

Reference request: EM algorithm and hidden Markov model books with solutions

I am studying missing data problems and the applications of the EM algorithm to missing data problems, like mixture models and hidden Markov models. We have been using Schafer's book Analysis of ...
0
votes
0answers
11 views

What are good tutorial on Weighted Finite Automata?

I would especially appreciate papers, books or tutorials with source code already available. Currently I'm reading "Spectral Learning Techniques for Weighted Automata, Transducers, and Grammars" by ...
1
vote
0answers
55 views

Hidden markov model multivariate regression with time-series data

I am working with a dataset that includes the trajectories of various car trips and would like to be able to predict their destinations using only a subset of the trip trajectory. For instance, if in ...
1
vote
0answers
62 views

How to use a Hidden Markov Model to detect state in a time series?

Questions Am I right in assuming that the emission probabilities will not be following a gaussian distribution for my particular problem? Obviously, I will need to train the model for state ...
0
votes
0answers
17 views

disease progression R markov chains

hello i have a dataframe, some of the columns include: remission,height,weight,time from diagnosis, age ethnicity, age, patient id remission is 1 or 0 just to be clear i want to fit an appropriate ...
1
vote
2answers
55 views

Markov chains vs. HMM

Markov chains makes sense to me, I can use them to model probabilistic state changes in real life problems. Then comes the HMM. HMMs are said to be more suitable to model many problems than MCs. ...
0
votes
1answer
38 views

Estimate core state transition probability matrix in partially observable Markov decision processes

I have a longitudinal data set of patients who have been monitored by a medical test over a year. The results of this test have false positive and false negative, so the system is partially ...
0
votes
0answers
14 views

Implications of using fixed effects to account for hierarchical data structure

I am currently implementing a hidden Markov model in R, using the msm package. The data I am using are drawn from a cluster-randomized trial; i.e. there is a ...
0
votes
0answers
29 views

Hidden Markov model question; pseudo time series?

I apologize that the title of this question isn't super specific, but I am having a very difficult time exactly and succinctly describing the problem I am facing in my implementation of a hidden ...
0
votes
0answers
28 views

Implementation of bag-of-features HMM?

I'm trying implement a word-spotting paper that uses a Hidden Markov Model where the emissions are a bag of words/features. I have found HMM implementations, but I haven't seen functionality to ...
0
votes
1answer
43 views

time series based classification

I want to classify some data. Basically the data is time series in nature. The target variable is categorical. I know there are so many algorithms for predicting the time series model. However, I have ...
0
votes
0answers
38 views

Observation Likelihood in hidden Markov models

As far as I understand, in discrete HMM, the observation symbol probability distribution $b_{i}(O_{t})$ is always a probability less than 1, e.g. $\frac{1}{6}$ for each side when rolling a dice. But ...
0
votes
0answers
30 views

Values of PDF in Bayes Classifier

I'm new here and also a beginner in statistics. I'm implementing a Bayes classifier for two classes but get confused with the value of likelihood (pdf). $$P(c|o) = p(o|c)\cdot P(c)/p(o);$$ Here ...
0
votes
0answers
74 views

Good library for Switching Autoregressive Hidden Markov Model (SAR-HMM)

can you recommend a good library for SAR-HMM? (Switching Autoregressive Hidden Markov Model) Apparently only MATLAB can be recommended. ...
1
vote
0answers
19 views

Hidden Markov models with state transitions conditioned on some node

I'm lacking some clarity related to HMM's Suppose I have a binomial state node and another binomial observation node, In this node the conditional probability table will be state transition matrix ...
0
votes
0answers
24 views

How to evaluate the goodness of Fit of parameters obtained from EM algorithm

I have a set of observations $\mathcal{Y} = {Y_1, \cdots, Y_T}$. I am running EM algorithm to fit the observations to the following Hidden Markov Model $$A = [a_{ij}]_{N \times N}, a_{ij} = P(X_{k+1} ...
0
votes
0answers
28 views

How to fit a stochastic matrix to given data.?

Given a data sequence of noisy observations of a 3-state Markov chain $X$ -- $y_1$,$y_2$,...$y_n$, with two transition matrices $A_1$ and $A_2$ corresponding to different regions (**) in the (unit) ...
0
votes
0answers
72 views

Hidden Markov Model For Text Classification

I have a question about HMMs being used to classify an entire text body under examination. This is as opposed to classifying a subset of a text body under examination. For example, classifying a news ...
3
votes
1answer
172 views

Selecting the number of mixtures / hidden states / latent variables

My question is regarding Gaussian Mixture models, Hidden Markov models (HMM) or any type of clustering or latent variable model, for which we can devise a likelihood function. Specifically, I train a ...
0
votes
0answers
15 views

How can we compare two probabilistic models(markov networks) such that its prediction(confidence) depends on amount of training data?

I have a task of comparing two CRF models where each node and edge probability is associated with reliability depending on amount of data it is trained .How can I have a confidence metric for ...
0
votes
0answers
29 views

Conditional distribution of current state of HMM given past observations and state

I want to compute the following conditional probabilities for an HMM, where I shall refer to the state at time $t$ as $X_t$ and the observation at time $t$ is $O_t$: $$\text{Pr}\left(X_t | O_1, ...
0
votes
0answers
21 views

How to Format Data for Structured Learning Problem?

I'm working on a project classifying discussion forum posts into various pre-defined categories, and would like to use a sequential learning model such as CRF's. I code mostly in Python and have found ...
0
votes
0answers
31 views

How long does it take two identical hidden Markov models run on same observations to forget their initial distributions (if ever)?

Let $H_1$ and $H_2$ be two instances of a finite Hidden Markov Model (HMM) $H$. That is, $H_1$ and $H_2$ have identical state spaces $Q$ as well as identical transition $A$ and emission probabilities ...
2
votes
1answer
267 views

Hidden Markov Model vs Markov Transition Model vs State-Space Model…?

For my master's thesis, I am working on developing a statistical model for the transitions between different states, defined by serological status. For now, I won't give too many details into this ...
0
votes
1answer
74 views

Is this a job for mixture of experts regression or semi-hidden markov models or something else?

Data I have several thousand timeseries each comprising around 365 data points. Browsing through a few of them, it looks like each timeseries consists of several regimes (different number f regimes ...
0
votes
1answer
44 views

make prediction with HMM

I want to use HMM to make some prediction. say $O$ is the observation, $S$ is the hidden states, and I know how to train the model with forward-backward algorithm. I just get confused with how to ...
4
votes
2answers
143 views

Finding occurrences of specific patterns in time series

I have to locate occurrences of Cyllinder, Bell and Funnel patterns in univariate time series $X$ of gamma-ray sensoring. This is a specific case of the general CBF synthetic problem found in a few ...
1
vote
0answers
26 views

Flow of influence in a v-structure for Probabilistic Graphical Models

I'm not very sure I understand why an observed v-structure have different flow of influence behaviour for a directed and an undirected graph. What is the intuition behind the actual definition for ...
2
votes
1answer
40 views

Hidden Markov Model to fill missing elements in a sequence

In my project I have a set of sequences (elements are letters from English alphabet) and some of the sequences have missing elements. I need to fill them with the most probable elements. I've been ...
2
votes
1answer
98 views

Can Hidden Markov Models be used to predict next observation?

I am reading up on Hidden Markov Models (HMMs) for my research and would like to know if it is applicable to the problem I wish to tackle. My problem is to detect/estimate the next value of a ...
0
votes
1answer
112 views

HMCM vs Viterbi algorithm for calculating most likely path of an HMM [duplicate]

My expertise in machine learning and statistics is probably at a sophomore level. But anyway, my question is this: Given a Hidden Markov Model returned over a sequence of events with some states, how ...
3
votes
0answers
75 views

Use of Hidden Markov Models for Clustering

I would like to ask whether Hidden Markov Models can be used for clustering and if so, in what cases. I have found somewhere, references like this but practically I haven't found a way to do this. Is ...
0
votes
0answers
15 views

Calculate probability distribution $p\left(\left.X_{1:T}\right|Z_{1:T},y_{1:T}\right)$ in linear- non-Gaussian state space model

I have a linear, non-Gaussian state space model. Observation equation: $y_{t}=a+bX_{t}+cZ_{t}+\epsilon_{t}$ $\,\,\,\,$ $\epsilon_{t}\sim\mathcal{N}\left(0,\omega^{2}\right)$ Transition equations: ...
0
votes
0answers
42 views

loglikelihood for HMM with continuous emissions

I have a HMM and that has continuous valued emissions. I model the emissions using Weibull distributions. After I run the HMM I get the states, transition probabilities, priors and shape,scale ...
3
votes
1answer
59 views

How do you find mathematical expressions for the posterior marginals i.e. $P(x_n|y_0, … , y_n)$ in an HMM?

My goal is to find closed form equations for posterior marginals $P(x_n|y_0, ... , y_n)$ in a general HMM. I was told that we can calculate it exactly via BP (belief propagation, thought not sure how ...
0
votes
0answers
26 views

What are the states and observation in HMM speech recognition?

For example: Given a two state HMM a and b If I define a -> b = # a -> a = # b -> b = # b -> a = # Pr(A|a) = # Pr(A|b) = # Pr(B|a) = # Pr(B|b) = # ...