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ocaml-gpr-devel-1.2.1-2.mga6.x86_64.rpm

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<link title="Gpr_version" rel="Chapter" href="Gpr_version.html"><title>Index of types</title>
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<h1>Index of types</h1>
<table>
<tr><td align="left"><br>C</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Model.html#TYPEco_variance_coeffs">co_variance_coeffs</a> [<a href="Gpr_interfaces.Sigs.Eval.Model.html">Gpr_interfaces.Sigs.Eval.Model</a>]</td>
<td><div class="info">
Type of covariance coefficients
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.html#TYPEcommon_mat_deriv">common_mat_deriv</a> [<a href="Gpr_interfaces.html">Gpr_interfaces</a>]</td>
<td><div class="info">
Derivative representations for both symmetric and unsymmetric matrices.
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Deriv.Inputs.html#TYPEcross">cross</a> [<a href="Gpr_interfaces.Specs.Deriv.Inputs.html">Gpr_interfaces.Specs.Deriv.Inputs</a>]</td>
<td><div class="info">
Representation of precomputed data for calculating the
                      derivative of the cross-covariance matrix between inputs
                      and inducing inputs.
</div>
</td></tr>
<tr><td align="left"><br>D</td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Deriv.Inputs.html#TYPEdiag">diag</a> [<a href="Gpr_interfaces.Specs.Deriv.Inputs.html">Gpr_interfaces.Specs.Deriv.Inputs</a>]</td>
<td><div class="info">
Representation of precomputed data for calculating the
                     derivative of the diagonal of the covariance matrix of
                     inputs.
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.html#TYPEdiag_deriv">diag_deriv</a> [<a href="Gpr_interfaces.html">Gpr_interfaces</a>]</td>
<td><div class="info">
Derivatives of diagonal matrices.
</div>
</td></tr>
<tr><td align="left"><br>F</td></tr>
<tr><td><a href="Gpr_utils.html#TYPEfast_float_ref">fast_float_ref</a> [<a href="Gpr_utils.html">Gpr_utils</a>]</td>
<td></td></tr>
<tr><td align="left"><br>H</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Deriv.Deriv.Trained.html#TYPEhyper_t">hyper_t</a> [<a href="Gpr_interfaces.Sigs.Deriv.Deriv.Trained.html">Gpr_interfaces.Sigs.Deriv.Deriv.Trained</a>]</td>
<td><div class="info">
Type of trained models for general hyper parameters
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Deriv.Deriv.Model.html#TYPEhyper_t">hyper_t</a> [<a href="Gpr_interfaces.Sigs.Deriv.Deriv.Model.html">Gpr_interfaces.Sigs.Deriv.Deriv.Model</a>]</td>
<td><div class="info">
Type of models for general hyper parameters
</div>
</td></tr>
<tr><td align="left"><br>I</td></tr>
<tr><td><a href="Gpr_cov_se_iso.html#TYPEinducing_hyper">inducing_hyper</a> [<a href="Gpr_cov_se_iso.html">Gpr_cov_se_iso</a>]</td>
<td></td></tr>
<tr><td align="left"><br>M</td></tr>
<tr><td><a href="Gpr_interfaces.html#TYPEmat_deriv">mat_deriv</a> [<a href="Gpr_interfaces.html">Gpr_interfaces</a>]</td>
<td><div class="info">
Only general matrices support sparse column representations.
</div>
</td></tr>
<tr><td align="left"><br>P</td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Kernel.html#TYPEparams">params</a> [<a href="Gpr_interfaces.Specs.Kernel.html">Gpr_interfaces.Specs.Kernel</a>]</td>
<td><div class="info">
Type of kernel parameters
</div>
</td></tr>
<tr><td><a href="Gpr_cov_se_fat.Params.html#TYPEparams">params</a> [<a href="Gpr_cov_se_fat.Params.html">Gpr_cov_se_fat.Params</a>]</td>
<td></td></tr>
<tr><td align="left"><br>S</td></tr>
<tr><td><a href="Gpr_interfaces.html#TYPEsymm_mat_deriv">symm_mat_deriv</a> [<a href="Gpr_interfaces.html">Gpr_interfaces</a>]</td>
<td><div class="info">
Only symmetric (square) matrices support diagonal vectors and
    diagonal constants as derivatives.
</div>
</td></tr>
<tr><td align="left"><br>T</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Optimizer.Optimizer.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Optimizer.Optimizer.html">Gpr_interfaces.Sigs.Optimizer.Optimizer</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Deriv.Deriv.Optim.SMD.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Deriv.Deriv.Optim.SMD.html">Gpr_interfaces.Sigs.Deriv.Deriv.Optim.SMD</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Deriv.Deriv.Optim.SGD.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Deriv.Deriv.Optim.SGD.html">Gpr_interfaces.Sigs.Deriv.Deriv.Optim.SGD</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Deriv.Deriv.Trained.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Deriv.Deriv.Trained.html">Gpr_interfaces.Sigs.Deriv.Deriv.Trained</a>]</td>
<td><div class="info">
Type of trained models with derivatives
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Deriv.Deriv.Model.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Deriv.Deriv.Model.html">Gpr_interfaces.Sigs.Deriv.Deriv.Model</a>]</td>
<td><div class="info">
Type of models with derivatives
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Deriv.Deriv.Inputs.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Deriv.Deriv.Inputs.html">Gpr_interfaces.Sigs.Deriv.Deriv.Inputs</a>]</td>
<td><div class="info">
Type of inputs with derivatives
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Deriv.Deriv.Inducing.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Deriv.Deriv.Inducing.html">Gpr_interfaces.Sigs.Deriv.Deriv.Inducing</a>]</td>
<td><div class="info">
Type of inducing inputs with derivatives
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Cov_sampler.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Cov_sampler.html">Gpr_interfaces.Sigs.Eval.Cov_sampler</a>]</td>
<td><div class="info">
Type of covariance sampler
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Sampler.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Sampler.html">Gpr_interfaces.Sigs.Eval.Sampler</a>]</td>
<td><div class="info">
Type of sampler
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Covariances.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Covariances.html">Gpr_interfaces.Sigs.Eval.Covariances</a>]</td>
<td><div class="info">
Type of covariances
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Variances.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Variances.html">Gpr_interfaces.Sigs.Eval.Variances</a>]</td>
<td><div class="info">
Type of variances
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Variance.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Variance.html">Gpr_interfaces.Sigs.Eval.Variance</a>]</td>
<td><div class="info">
Type of variance
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Co_variance_predictor.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Co_variance_predictor.html">Gpr_interfaces.Sigs.Eval.Co_variance_predictor</a>]</td>
<td><div class="info">
Type of (co-)variance predictor
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Means.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Means.html">Gpr_interfaces.Sigs.Eval.Means</a>]</td>
<td><div class="info">
Type of means
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Mean.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Mean.html">Gpr_interfaces.Sigs.Eval.Mean</a>]</td>
<td><div class="info">
Type of mean
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Mean_predictor.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Mean_predictor.html">Gpr_interfaces.Sigs.Eval.Mean_predictor</a>]</td>
<td><div class="info">
Type of mean predictors
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Stats.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Stats.html">Gpr_interfaces.Sigs.Eval.Stats</a>]</td>
<td><div class="info">
Type of full statistics
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Trained.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Trained.html">Gpr_interfaces.Sigs.Eval.Trained</a>]</td>
<td><div class="info">
Type of trained models
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Model.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Model.html">Gpr_interfaces.Sigs.Eval.Model</a>]</td>
<td><div class="info">
Type of models
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Inputs.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Inputs.html">Gpr_interfaces.Sigs.Eval.Inputs</a>]</td>
<td><div class="info">
Type of (multiple) inputs
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Input.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Input.html">Gpr_interfaces.Sigs.Eval.Input</a>]</td>
<td><div class="info">
Type of single input
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Sigs.Eval.Inducing.html#TYPEt">t</a> [<a href="Gpr_interfaces.Sigs.Eval.Inducing.html">Gpr_interfaces.Sigs.Eval.Inducing</a>]</td>
<td><div class="info">
Type of inducing inputs
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Optimizer.Var.html#TYPEt">t</a> [<a href="Gpr_interfaces.Specs.Optimizer.Var.html">Gpr_interfaces.Specs.Optimizer.Var</a>]</td>
<td><div class="info">
Type of input parameter
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Deriv.Hyper.html#TYPEt">t</a> [<a href="Gpr_interfaces.Specs.Deriv.Hyper.html">Gpr_interfaces.Specs.Deriv.Hyper</a>]</td>
<td><div class="info">
Type of hyper parameter
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Eval.Inputs.html#TYPEt">t</a> [<a href="Gpr_interfaces.Specs.Eval.Inputs.html">Gpr_interfaces.Specs.Eval.Inputs</a>]</td>
<td><div class="info">
Type of input points
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Eval.Input.html#TYPEt">t</a> [<a href="Gpr_interfaces.Specs.Eval.Input.html">Gpr_interfaces.Specs.Eval.Input</a>]</td>
<td><div class="info">
Type of input point
</div>
</td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Eval.Inducing.html#TYPEt">t</a> [<a href="Gpr_interfaces.Specs.Eval.Inducing.html">Gpr_interfaces.Specs.Eval.Inducing</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Kernel.html#TYPEt">t</a> [<a href="Gpr_interfaces.Specs.Kernel.html">Gpr_interfaces.Specs.Kernel</a>]</td>
<td><div class="info">
Type of kernel
</div>
</td></tr>
<tr><td><a href="Gpr_utils.Int_vec.html#TYPEt">t</a> [<a href="Gpr_utils.Int_vec.html">Gpr_utils.Int_vec</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_cov_se_iso.Params.html#TYPEt">t</a> [<a href="Gpr_cov_se_iso.Params.html">Gpr_cov_se_iso.Params</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_cov_se_fat.Hyper_repr.html#TYPEt">t</a> [<a href="Gpr_cov_se_fat.Hyper_repr.html">Gpr_cov_se_fat.Hyper_repr</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_cov_se_fat.Inducing_hyper.html#TYPEt">t</a> [<a href="Gpr_cov_se_fat.Inducing_hyper.html">Gpr_cov_se_fat.Inducing_hyper</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_cov_se_fat.Dim_hyper.html#TYPEt">t</a> [<a href="Gpr_cov_se_fat.Dim_hyper.html">Gpr_cov_se_fat.Dim_hyper</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_cov_se_fat.Proj_hyper.html#TYPEt">t</a> [<a href="Gpr_cov_se_fat.Proj_hyper.html">Gpr_cov_se_fat.Proj_hyper</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_cov_se_fat.Params.html#TYPEt">t</a> [<a href="Gpr_cov_se_fat.Params.html">Gpr_cov_se_fat.Params</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_cov_lin_one.Params.html#TYPEt">t</a> [<a href="Gpr_cov_lin_one.Params.html">Gpr_cov_lin_one.Params</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_cov_lin_ard.Params.html#TYPEt">t</a> [<a href="Gpr_cov_lin_ard.Params.html">Gpr_cov_lin_ard.Params</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_cov_const.Params.html#TYPEt">t</a> [<a href="Gpr_cov_const.Params.html">Gpr_cov_const.Params</a>]</td>
<td></td></tr>
<tr><td><a href="Gpr_block_diag.html#TYPEt">t</a> [<a href="Gpr_block_diag.html">Gpr_block_diag</a>]</td>
<td><div class="info">
Type of block diagonal matrices
</div>
</td></tr>
<tr><td align="left"><br>U</td></tr>
<tr><td><a href="Gpr_interfaces.Specs.Deriv.Inducing.html#TYPEupper">upper</a> [<a href="Gpr_interfaces.Specs.Deriv.Inducing.html">Gpr_interfaces.Specs.Deriv.Inducing</a>]</td>
<td><div class="info">
Representation of precomputed data for calculating the
                      upper triangle of the derivative of the covariance matrix
                      of inducing inputs.
</div>
</td></tr>
</table>
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