mbcmodel.localmodel

Properties and methods for local model objects

Description

Use these properties and object functions to create and examine local model objects.

Creation

Syntax

LMObj = mbcmodel.CreateModel.(LocalModelType,Inputs)

Description

LMObj = mbcmodel.CreateModel.(LocalModelType,Inputs) creates an mbcmodel.localmodel object of local model type LocalModelType and inputs Inputs.

For a list of model types, see CreateModel.

Properties

expand all

`Type` — Type of model objects
vector

This property is read-only.

Type of model objects to be returned to mbcmodel.project, specified as a vector. model.Type returns the model type.

Note

Spaces and case in model Type are ignored.

The model type must be one in this table.

`Type`	Model Object
Polynomial	`mbcmodel.linearmodel`
Hybrid Spline	`mbcmodel.linearmodel`
RBF	`mbcmodel.linearmodel`
Hybrid RBF	`mbcmodel.linearmodel`
Polynomial-RBF	`mbcmodel.linearmodel`
Hybrid Spline-RBF	`mbcmodel.linearmodel`
Gaussian Process	`mbcmodel.model`
Free Knot Spline	`mbcmodel.model`
Transient	`mbcmodel.model`
User-Defined	`mbcmodel.model`
Neural Network	`mbcmodel.model`
Interpolating RBF	`mbcmodel.model`
Local Polynomial Spline	`mbcmodel.localmodel`
Local Polynomial with Datum	`mbcmodel.localmodel`
Local Polynomial	`mbcmodel.localmodel`
Local Hybrid Spline	`mbcmodel.localmodel`
Local Truncated Power Series	`mbcmodel.localmodel`
Local Free Knot Spline	`mbcmodel.localmodel`
Local Multiple Models	`mbcmodel.localmodel`
Local Growth	`mbcmodel.localmodel`
Local User-Defined	`mbcmodel.localmodel`
Local Transient	`mbcmodel.localmodel`
Local Average Fit	`mbcmodel.localmodel`

You can get a list of types by using getAlternativeTypes. Use this syntax.

Mlist = getAlternativeTypes(M)

In this syntax, M is an mbcmodel.model object.

Data Types: char | string

`Status` — Status of model fit
`Not Fitted` | `Fitted` | `Best`

This property is read-only.

Status of model fit, specified as Not Fitted, Fitted, or Best.

Data Types: char | string

`NumInputs` — Number of inputs to model
real positive scalar

This property is read-only.

Number of inputs to model, specified as a real positive scalar.

Data Types: double | single

`InputData` — Input training data
matrix

This property is read-only.

Input training data, specified as a matrix. InputData is specified when calling fit.

Data Types: double

`OutputData` — Output or response data
matrix

This property is read-only.

Output or response data, specified as a matrix. OutputData is specified when calling fit.

Data Types: double

`Properties` — Local model properties
`mbcmodel.modelproperties` object

Local model properties, specified as an mbcmodel.modelproperties object. Every local model object has an mbcmodel.modelproperties object. In this object, each local model type has specific properties, as described in these tables.

Local Polynomial Properties

`Property`	Description
Order	Polynomial order (vector int: `{[0,Inf],2}`)
InteractionOrder	Maximum order of interaction terms (int: `[0,Inf]`)
TransformInputRange	Transform inputs (Boolean)
ParameterNames	List of parameter names (read-only)
StepwiseStatus	Stepwise status `{'Always','Never','Step'}` (cell)
Transform	Transform function (char) or empty (`''`)
CovarianceModel	Covariance model (enum: `{'None','Power','Exponential','Mixed'}`)
CorrelationModel	Correlation model (enum: `{'None','MA(1)','AR(1)','AR(2)'}`)

Local Hybrid Spline Properties

`Property`	Description
Order	Spline and polynomial order (vector int: `{[0,3],2}`)
SplineVariable	Spline variable
SplineInteraction	Order of interaction between spline and polynomial (int: `[0,3]`)
Knots: Position of knots (vector real)	`ParameterNames`: List of parameter names (read-only)
StepwiseStatus	Stepwise status `{'Always','Never','Step'}` (cell)
Transform	Transform function (char) or empty (`''`)
CovarianceModel	Covariance model (enum: `{'None','Power','Exponential','Mixed'}`)
CorrelationModel	Correlation model (enum: `{'None','MA(1)','AR(1)','AR(2)'}`)

Local Polynomial Spline Properties

`Property`	Description
HighOrder	Polynomial order above knot (int: `[2,Inf]`)
LowOrder	Polynomial order below knot (int: `[2,Inf]`)
Transform	Transform function (char) or empty (`''`)
CovarianceModel	Covariance model (enum: `{'None','Power','Exponential','Mixed'}`)
CorrelationModel	Correlation model (enum: `{'None','MA(1)','AR(1)','AR(2)'}`)
DatumType	Datum Type (enum: `{'None','Maximum','Minimum','Linked'}`)

Local Polynomial With Datum Properties

`Property`	Description
Order	Polynomial order (int: `[0,Inf]`)
Transform	Transform function (char) or empty (`''`)
CovarianceModel	Covariance model (enum: `{'None','Power','Exponential','Mixed'}`)
CorrelationModel	Correlation model (enum: `{'None','MA(1)','AR(1)','AR(2)'}`)
DatumType	Datum type (enum: `{'None','Maximum','Minimum'`,`'Linked'}`)

Local Free Knot Spline Properties

`Property`	Description
Order	Spline order (int: `[0,Inf]`)
NumKnots	Number of knots (int: `'Positive'`)
Transform	Transform function (char) or empty (`''`)
CovarianceModel	Covariance model (enum: `{'None','Power','Exponential','Mixed'}`)
CorrelationModel	Correlation model (enum: `{'None','MA(1)','AR(1)','AR(2)'}`)

Local Truncated Power Series Properties

`Property`	Description
Order	Polynomial order (int: `'Positive'`)
NumKnots	Number of knots (int: `'Positive'`)
Transform	Transform function (char) or empty (`''`)
CovarianceModel	Covariance model (enum: `{'None','Power','Exponential','Mixed'}`)
CorrelationModel	Correlation model (enum: `{'None','MA(1)','AR(1)','AR(2)'}`)

Local Growth Properties

`Property`	Description
Model	Growth model (enum: `{'expgrowth','gomp','logistic','logistic4','mmf','richards','weibul'}`)
AlternativeModels	List of growth models (read-only)
Transform	Transform function (char) or empty (`''`)
TransformBothSides	Transform both sides (Boolean)
CovarianceModel	Covariance Model (enum: `{'None','Power','Exponential','Mixed'}`)
CorrelationModel	Correlation Model (enum: `{'None','MA(1)','AR(1)','AR(2)'}`)

Local User-Defined Properties

`Property`	Description
Model	Name of user-defined model (enum: `{'exponential'}`)
AlternativeModels	List of registered user-defined models (read-only)
Transform	Transform function (char) or empty (`''`)
TransformBothSides	Transform both sides (Boolean)
CovarianceModel	Covariance model (enum: `{'None','Power','Exponential','Mixed'}`)
CorrelationModel	Correlation model (enum: `{'None','MA(1)','AR(1)','AR(2)'}`)

Local Transient Properties

`Property`	Description
Model	Name of transient model (enum: `{'fuelPuddle'}`)
AlternativeModels	List of registered transient models (read-only)
Transform	Transform function (char) or empty (`''`)
TransformBothSides	Transform both sides (Boolean)
CovarianceModel	Covariance model (enum: `{'None','Power','Exponential','Mixed'}`)
CorrelationModel	Correlation model (enum: `{'None','MA(1)','AR(1)','AR(2)'}`)

Local Multiple Models Properties

`Property`	Description
ModelCandidates	List of candidate models (cell)
SelectionStatistic	Selection statistic for automatic model selection (char). See the list for input names and descriptions. The list of valid statistics is the summary statistics in common with all model candidates. For example, if an interpolating RBF is one of the candidates, only RMSE is available.
AutomaticInputRanges	Use data range as model input ranges (Boolean)
Transform	Transform function (char) or empty (`''`)

Model Type	List of `SelectionStatistic` Inputs
Polynomial, Hybrid Spline, RBF, Hybrid RBF	`'PRESS RMSE','RMSE','GCV','Weighted PRESS','-2logL','AIC','AICc'`,`'BIC','R^2','R^2 adj','PRESS R^2','DW','Cp','cond(J)'`
Neural Network	`'RMSE','R^2','R^2 adj','-2logL','AIC','AICc','BIC'`
Free Knot Spline	`'PRESS RMSE','RMSE','GCV','Weighted PRESS','-2logL','AIC','AICc','BIC','R^2','R^2 adj','PRESS R^2','DW','Cp'`
Interpolating RBF	`'RMSE'`

`SelectionStatistic` Input Argument	Description
`'PRESS RMSE'`	Predicted standard error	`'sqrt(PRESS/N)'`
`'RMSE'`	Root mean squared error	`'sqrt(SSE/(N-p))'`
`'GCV'`	Generalized cross-validation variance	`'N*SSE/(N-p)^2'`
`'Weighted PRESS'`	Weighted predicted standard error	`'sqrt(PRESS/(N-p-1))'`
`'-2logL'`	-2 * log likelihood	`'N*log(SSE/N)'`
`'AIC'`	Akaike information criteria	`'-2logL + 2*(p+1)'`
`'AICc'`	Small sample Akaike information criteria	`'-2logL + 2(p+1)*N/(N-p)'`
`'BIC'`	Bayesian information criteria	`'-2logL + 2log(N)(p+1)'`
`'R^2'`	R^2	`'1 - SSE/SST'`
`'R^2 adj'`	Adjusted R^2	`'1 - SSE/SST*(N-1)/(N-p)'`
`'PRESS R^2'`	PRESS R^2	`'1 - PRESS/SST'`
`'DW'`	Durbin-Watson statistic	`'sum((e_i-e_{i+1})^2)/sum(e_i^2) '`
`'Cp'`	Mallow's statistic	`'SSE/(SSEmax/(N-pmax)) - N + 2*p'`
`'cond(J)'`	Condition of regression matrix	`'cond(J)'`

Local Average Fit Properties

`Property`	Description
Model	[1x1 `mbcmodel.linearmodel`]
Transform	Transform function (char) or empty (`''`)

Data Types: char | string

`FitAlgorithm` — Fit algorithm for model
`mbcmodel.FitAlgorithm` object

Fit algorithm for model, specified as an mbcmodel.model.FitAlgorithm object.

FitAlgorithm is a property of mbcmodel.model and of boundary model objects mbcboundary.AbstractBoundary and all subclasses.

An mbcmodel.model.FitAlgorithm object is contained within the FitAlgorithm property of an mbcmodel.model object or mbcboundary object.

As an alternative to using CreateAlgorithm, you can assign the algorithm name directly to the algorithm.

B.FitAlgorithm.BoundaryPointOptions = 'Boundary Only';

m.FitAlgorithm = 'Minimize PRESS';

Case and spaces are ignored.

To get a fitalgorithm object, F, from a model, use this code.

M = mbcmodel.CreateModel('Polynomial', 4);
F = M.FitAlgorithm

F = 
Algorithm: Least Squares
Alternatives: 'Minimize PRESS','Forward Selection','Backward 
Selection','Prune'
1x1 struct array with no fields.

`Inputs` — Model input
`mbcmodel.modelinput` object

Model input, specified as an mbcmodel.modelinput object.

`Name` — Model object name
character vector

Model object name, specified as a character vector.

Data Types: char | string

`Units` — Model output unit
vector

Model output unit, specified as a vector.

Data Types: double | single

`Response` — Response object
object

This property is read-only.

Response object in mbcmodel.project object, specified as an object.

`IsBeingEdited` — Boolean indicating whether model is being edited
`true` or `1` | `false` or `0`

This property is read-only.

Boolean indicating whether model is being edited, specified as either true (1) or false (0).

Example: 0

Data Types: logical

`ResponseFeatures` — Response features for local model object
`mbcmodel.responsefeatures` object

Response features for local model object, specified as an mbcmodel.responsefeatures object. Each local model type has specific response features.

Data Types: char | string

Object Functions

`fit`	Fit model or boundary model to new or existing data, and provide summary statistics
`SummaryStatistics`	Summary statistics for response

Version History

Introduced before R2006a

mbcmodel.localmodel

Description

Creation

Syntax

Description

Properties

Type — Type of model objects vector

Status — Status of model fit Not Fitted | Fitted | Best

NumInputs — Number of inputs to model real positive scalar

InputData — Input training data matrix

OutputData — Output or response data matrix

Properties — Local model properties mbcmodel.modelproperties object

FitAlgorithm — Fit algorithm for model mbcmodel.FitAlgorithm object

Inputs — Model input mbcmodel.modelinput object

Name — Model object name character vector

Units — Model output unit vector

Response — Response object object

IsBeingEdited — Boolean indicating whether model is being edited true or 1 | false or 0

ResponseFeatures — Response features for local model object mbcmodel.responsefeatures object

Object Functions

Version History

See Also

`Type` — Type of model objects
vector

`Status` — Status of model fit
`Not Fitted` | `Fitted` | `Best`

`NumInputs` — Number of inputs to model
real positive scalar

`InputData` — Input training data
matrix

`OutputData` — Output or response data
matrix

`Properties` — Local model properties
`mbcmodel.modelproperties` object

`FitAlgorithm` — Fit algorithm for model
`mbcmodel.FitAlgorithm` object

`Inputs` — Model input
`mbcmodel.modelinput` object

`Name` — Model object name
character vector

`Units` — Model output unit
vector

`Response` — Response object
object

`IsBeingEdited` — Boolean indicating whether model is being edited
`true` or `1` | `false` or `0`

`ResponseFeatures` — Response features for local model object
`mbcmodel.responsefeatures` object