Description Usage Arguments Value Author(s) References Examples

Function that performs local and global decoding (Viterbi) from the output of `est_lm_basic`

, `est_lm_cov_latent`

, `est_lm_cov_manifest`

, and `est_lm_mixed`

.

**The function is no longer maintained. Please look at** `lmestDecoding`

**function**

1 |

`est ` |
output from |

`Y ` |
single vector or matrix of responses |

`X1 ` |
matrix of covariates on the initial probabilities ( |

`X2 ` |
array of covariates on the transition probabilites |

`fort ` |
to use Fortran routines |

`Ul ` |
matrix of local decoded states corresponding to each row of Y |

`Ug ` |
matrix of global decoded states corresponding to each row of Y |

Francesco Bartolucci, Silvia Pandolfi, University of Perugia (IT), http://www.stat.unipg.it/bartolucci

Viterbi A. (1967) Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm. *IEEE Transactions on Information Theory*, **13**, 260-269.

Juan B., Rabiner L. (1991) Hidden Markov Models for Speech Recognition. *Technometrics*, **33**, 251-272.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 | ```
## Not run:
# example for the output from est_lm_basic
data(data_drug)
data_drug <- as.matrix(data_drug)
S <- data_drug[,1:5]-1
yv <- data_drug[,6]
n <- sum(yv)
# fit the Basic LM model
k <- 3
est <- est_lm_basic(S, yv, k, mod = 1)
# decoding for a single sequence
out1 <- decoding(est, S[1,])
# decoding for all sequences
out2 <- decoding(est, S)
# example for the output from est_lm_cov_latent with difflogit parametrization
data(data_SRHS_long)
dataSRHS <- data_SRHS_long[1:1600,]
TT <- 8
head(dataSRHS)
res <- long2matrices(dataSRHS$id, X = cbind(dataSRHS$gender-1,
dataSRHS$race == 2 | dataSRHS$race == 3, dataSRHS$education == 4,
dataSRHS$education == 5, dataSRHS$age-50,(dataSRHS$age-50)^2/100),
Y= dataSRHS$srhs)
# matrix of responses (with ordered categories from 0 to 4)
S <- 5-res$YY
# matrix of covariates (for the first and the following occasions)
# colums are: gender,race,educational level (2 columns),age,age^2)
X1 <- res$XX[,1,]
X2 <- res$XX[,2:TT,]
# estimate the model
est <- est_lm_cov_latent(S, X1, X2, k = 2, output = TRUE, param = "difflogit")
# decoding for a single sequence
out1 <- decoding(est, S[1,,], X1[1,], X2[1,,])
# decoding for all sequences
out2 <- decoding(est, S, X1, X2)
## End(Not run)
``` |

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