bpr_optimize {BPRMeth} | R Documentation

## (DEPRECATED) Optimize BPR negative log likelihood function

### Description

(DEPRECATED) The function bpr_optimize minimizes the negative log likelihood of the BPR function. Since it cannot be evaluated analytically, an optimization procedure is used. The `optim` packages is used for performing optimization.

### Usage

    bpr_optim(x, ...)

    ## S3 method for class 'list'
    bpr_optim(
      x,
      w = NULL,
      basis = NULL,
      lambda = 1/2,
      opt_method = "CG",
      opt_itnmax = 100,
      is_parallel = TRUE,
      no_cores = NULL,
      ...
    )

    ## S3 method for class 'matrix'
    bpr_optim(
      x,
      w = NULL,
      basis = NULL,
      lambda = 1/2,
      opt_method = "CG",
      opt_itnmax = 100,
      ...
    )

### Arguments

`x` | The input object, either a `matrix` or a `list`.
`...` | Additional parameters.
`w` | A vector of parameters (i.e. coefficients of the basis functions)
`basis` | A 'basis' object. E.g. see `create_rbf_object`.
`lambda` | The complexity penalty coefficient for ridge regression.
`opt_method` | The optimization method to be used. See `optim` for possible methods. Default is "CG".
`opt_itnmax` | Optional argument giving the maximum number of iterations for the corresponding method. See `optim` for details.
`is_parallel` | Logical, indicating if code should be run in parallel.
`no_cores` | Number of cores to be used, default is max_no_cores - 2.

### Value

Depending on the input object `x`:

- If `x` is a `list`: An object containing the following elements:

  - `W_opt`: An Nx(M+1) matrix with the optimized parameter values. Each row of the matrix corresponds to each element of the list x. The columns are of the same length as the parameter vector w (i.e. number of basis functions).

  - `Mus`: An N x M matrix with the RBF centers if basis object is `create_rbf_object`, otherwise NULL.

  - `basis`: The basis object.

  - `w`: The initial values of the parameters w.

- If `x` is a `matrix`: An object containing the following elements:

  - `w_opt`: Optimized values for the coefficient vector w. The length of the result is the same as the length of the vector w.

  - `basis`: The basis object.

- If calling `bpr_optim_fast` just the optimal weight matrix W_opt.

### Author(s)

C.A.Kapourani C.A.Kapourani@ed.ac.uk

### See Also

`create_basis`, `eval_functions`

### Examples

    # Example of optimizing parameters for synthetic data using default values
    data <- meth_data
    out_opt <- bpr_optim(x = data, is_parallel = FALSE, opt_itnmax = 3)

    #-------------------------------------

    # Example of optimizing parameters for synthetic data using 3 RBFs
    ex_data <- meth_data
    basis <- create_rbf_object(M=3)
    out_opt <- bpr_optim(x = ex_data, is_parallel = FALSE, basis = basis,
                         opt_itnmax = 3)

    #-------------------------------------

    # Example of of specific promoter region using 2 RBFs
    basis <- create_rbf_object(M=2)
    w <- c(0.1, 0.1, 0.1)
    data <- meth_data[[1]]
    out_opt <- bpr_optim(x = data, w = w, basis = basis, fit_feature = "NLL",
                         opt_itnmax = 3)

[Package BPRMeth version 1.16.0 Index]