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stk_covmat_noise


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 STK_COVMAT_NOISE [STK internal]

 CALL: [K, P1, P2] = stk_covmat_noise (M, X1, X2, DIFF, PAIRWISE)

 INTERNAL FUNCTION WARNING:
    This function is currently considered as internal: API-breaking changes are
    likely to happen in future releases.  Please don't rely on it directly.



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 STK_COVMAT_NOISE [STK internal]



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stk_get_input_data


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 STK_GET_INTPUT_DATA returns the input data of a model

 CALL: INPUT_DATA = stk_get_input_data (MODEL)

    returns the INPUT_DATA of the MODEL (which is empty if MODEL is
    a prior model).

 See also: stk_get_output_data, stk_get_prior_model



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 STK_GET_INTPUT_DATA returns the input data of a model



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stk_get_observation_variances


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 STK_GET_OBSERVATION_VARIANCES returns the variance of the observations

 CALL: V = stk_get_observation_variances (MODEL)

    returns the variance of the observations that have been used to build
    the MODEL.  The result is empty if MODEL is a prior model.



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 STK_GET_OBSERVATION_VARIANCES returns the variance of the observations



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stk_get_optimizable_model_parameters


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 STK_GET_OPTIMIZABLE_PARAMETERS [STK internal]

 INTERNAL FUNCTION WARNING:

    This function is currently considered as internal.  STK users that wish to
    experiment with parameter classes can already overload it, but should be
    aware that API-breaking changes are likely to happen in future releases.

 See also: stk_get_optimizable_parameters



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 STK_GET_OPTIMIZABLE_PARAMETERS [STK internal]



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stk_get_optimizable_noise_parameters


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 STK_GET_OPTIMIZABLE_NOISE_PARAMETERS [STK internal]



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 STK_GET_OPTIMIZABLE_NOISE_PARAMETERS [STK internal]




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stk_get_output_data


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 STK_GET_OUTPUT_DATA returns the output data of a model

 CALL: OUTPUT_DATA = stk_get_output_data (MODEL)

    returns the OUTPUT_DATA of the MODEL (which is empty if MODEL is
    a prior model).

 See also: stk_get_input_data, stk_get_prior_model



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 STK_GET_OUTPUT_DATA returns the output data of a model



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stk_get_prior_model


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 STK_GET_PRIOR_MODEL returns the underlying prior model of a model

 CALL: PRIOR_MODEL = stk_get_prior_model (MODEL)

    returns the underlying PRIOR_MODEL of the MODEL (which is equal to MODEL
    itself if MODEL is a prior model).

 See also: stk_get_input_data, stk_get_output_data



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 STK_GET_PRIOR_MODEL returns the underlying prior model of a model



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stk_isnoisy


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 STK_ISNOISY returns false for noiseless models, true otherwise

 CALL: ISNOISY = stk_isnoisy (MODEL)

    returns false for a noiseless MODEL and true otherwise.

    MODEL is considered noiseless if:

     * MODEL.lognoisevariance is missing or empty  (for backward compatibility
       with previous versions of STK where the lognoisevariance field was
       optional),

     * MODEL.lognoisevariance is equal to -inf  (this is the default for a
       model created by stk_model and the currently recommended way to declare
       a noiseless model),

     * MODEL.lognoisevariance is a vector of -inf  (heteroscedastic case with
       all variances set to zero).

 REMARK: Variance model objects

    Note that in the case where MODEL.lognoisevariance is an object, the MODEL
    is automatically considered noisy, even when the parameters of the variance
    model are set (or can be set) to values such that the noise variance
    function vanishes.

 See also: stk_model



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 STK_ISNOISY returns false for noiseless models, true otherwise



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stk_model


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 STK_MODEL generates a model with default covariance parameters

 CALL: MODEL = stk_model ()

   returns a structure MODEL (see below for a description of the fields in such
   a structure) corresponding to one-dimensional Gaussian process prior with a
   constant but unknown mean ("ordinary" kriging) and a stationary Matern
   covariance function.

 CALL: MODEL = stk_model (COVARIANCE_TYPE)

   uses the user-supplied COVARIANCE_TYPE instead of the default.

 CALL: MODEL = stk_model (COVARIANCE_TYPE, DIM)

   creates a DIM-dimensional model. Note that, for DIM > 1, anisotropic
   covariance functions are provided with default parameters that make them
   isotropic.

 In STK, a Gaussian process model is described by a 'model' structure,
 which has mandatory fields and optional fields.

   MANDATORY FIELDS: covariance_type, param, lm, lognoisevariance
   OPTIONAL FIELD: param_prior, noise_prior

 See also stk_materncov_iso, stk_materncov_aniso, ...



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 STK_MODEL generates a model with default covariance parameters



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stk_model_fixlm


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 STK_MODEL_FIXLM [STK internal]

 This internal STK function ensures backward compatiblity for model structures
 with a .order field.



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 STK_MODEL_FIXLM [STK internal]



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stk_ortho_func


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 STK_ORTHO_FUNC [deprecated]

 CALL: P = stk_ortho_func (MODEL, X)

    computes the design matrix for the linear part of model MODEL at the set of
    evaluation points X. In general (see special case below), X is expected to
    be a structure, whose field 'a' contains the actual numerical data as an N
    x DIM matrix, where N is the number of evaluation points and and DIM the
    dimension of the space of factors. A matrix P of size N x L is returned,
    where L is the number of regression functions in the linear part of the
    model; e.g., L = 1 if MODEL.order is zero (ordinary kriging).

 DEPRECATION WARNINGS:

    The use of a .order field in model structures is deprecated and will be
    removed in a future release of STK.  The recommended approach is now to use
    a .lm field, which contains a function handle or any object that behaves
    like one (see stk_lm_*).

    stk_orth_func is deprecated and will be removed from future versions of
    STK (http://sourceforge.net/p/kriging/tickets/12).

 See also stk_make_matcov



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 STK_ORTHO_FUNC [deprecated]



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stk_predict_


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 STK_PREDICT_ [STK internal]

 See also: stk_predict



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 STK_PREDICT_ [STK internal]



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stk_set_optimizable_model_parameters


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 STK_SET_OPTIMIZABLE_PARAMETERS [STK internal]

 INTERNAL FUNCTION WARNING:

    This function is currently considered as internal.  STK users that wish to
    experiment with parameter classes can already overload it, but should be
    aware that API-breaking changes are likely to happen in future releases.

 See also: stk_set_optimizable_parameters



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 STK_SET_OPTIMIZABLE_PARAMETERS [STK internal]





