Synthetically generated dataset containing values of dependent variable
<code>x_t</code> given values of 
<code>x_t-1, x_t-2, ..., x_t-15</code>.

datasets

Methods and tools for analysing and validating the outputs
and modelled functions of artificial neural networks (ANNs) in terms
of predictive, replicative and structural validity. Also provides a
method for fitting feed-forward ANNs with a single hidden layer.

Patrice Kiener

validann

Validation Tools for Artificial Neural Networks

Greer B. Humphrey

ar9 function

A data frame with 1000 rows and 16 variables:<dl>
 <dt>x_t-1,x_t-2,x_t-3,x_t-4,x_t-5,x_t-6,x_t-7,x_t-8,x_t-9,x_t-10,x_t-11,x_t-12,</dt>
<dd></dd> <dt>x_t-13,x_t-14,x_t-15</dt>
<dd>lagged values of
 x_t in columns 1:15</dd> <dt>x_t</dt>
<dd>dependent variable in column 16</dd>
</dl>

Format

Synthetically generated dataset containing values of dependent variable
<code>x_t</code> given values of 
<code>x_t-1, x_t-2, ..., x_t-15</code>.

Data generated by autoregressive AR9 model. — ar9

A data frame with 1000 rows and 16 variables:<dl>
 <dt>x_t-1,x_t-2,x_t-3,x_t-4,x_t-5,x_t-6,x_t-7,x_t-8,x_t-9,x_t-10,x_t-11,x_t-12,</dt>
<dd></dd>

 <dt>x_t-13,x_t-14,x_t-15</dt>
<dd>lagged values of
 x_t in columns 1:15</dd>

 <dt>x_t</dt>
<dd>dependent variable in column 16</dd>


</dl>

ar9: Data generated by autoregressive AR9 model.

Description

Arguments

Format

Details

References

Examples