# seq_sim: Compute similarity scores between sequences of integers In stringdist: Approximate String Matching, Fuzzy Text Search, and String Distance Functions

## Description

Compute similarity scores between sequences of integers

## Usage

 ```1 2 3 4 5 6 7``` ```seq_sim( a, b, method = c("osa", "lv", "dl", "hamming", "lcs", "qgram", "cosine", "jaccard", "jw"), q = 1, ... ) ```

## Arguments

 `a` `list` of `integer` vectors (target) `b` `list` of `integer` vectors (source). Optional for `seq_distmatrix`. `method` Method for distance calculation. The default is `"osa"`, see `stringdist-metrics`. `q` Size of the q-gram; must be nonnegative. Only applies to `method='qgram'`, `'jaccard'` or `'cosine'`. `...` additional arguments are passed on to `seq_dist`.

## Value

A `numeric` vector of length `max(length(a),length(b))`. If one of the entries in `a` or `b` is `NA_integer_`, all comparisons with that element result in `NA`. Missings occurring within the sequences are treated as an ordinary number (the representation of `NA_integer_`).

`seq_dist`, `seq_amatch`
 ```1 2 3 4 5 6 7 8``` ```L1 <- list(1:3,2:4) L2 <- list(1:3) seq_sim(L1,L2,method="osa") # note how missing values are handled (L2 is recycled over L1) L1 <- list(c(1L,NA_integer_,3L),2:4,NA_integer_) L2 <- list(1:3) seq_sim(L1,L2) ```