Alex Falcao > Statistics-Forecast > Statistics::Forecast
Module Version: 0.3

# NAME

Statistics::Forecast - calculates a future value

# DESCRIPTION

This is a dummy Oriented Object module that calculates a future value by using existing values. The new value is calculated by using linear regression.

# SYNOPSIS

`   use Statistics::Forecast;`

Create forecast object

`   my \$FCAST = Statistics::Forecast->new("My Forecast Name");`

```   \$FCAST->{DataX} = \@Array_X;
\$FCAST->{DataY} = \@Array_Y;
\$FCAST->{NextX} = \$NextX;```

Calculate the result

`   \$FCAST->calc;`

Get the result

`   my \$Result_Forecast = \$FCAST->{ForecastY);`

# INTERNALS

The equation for Forecast is:

```   a+bx, where 'x' is the predicted value and
_    _
a = y + bx

b = sum((x+x)(y-y))/sum(x-x)**2```

# METHODS

new

Receives a forecast name, only to remember and returns the blessed data structure as a Statistics::Forecast object.

` my \$FCAST = Statistics::Forecast->new("My Forecast");`
calc

Calculate and return the forecast value.

` \$FCAST->calc;`
dump

Prints data for debuging propose.

` \$FCAST->dump;`
SumX

Returns the sum of X values.

` my \$SumOfX = \$FCAST->{SumX};`
SumY

Returns the sum of Y values.

` my \$SumOfY = \$FCAST->{SumY};`
SumXX

Returns the sum of X**2 values.

` my \$SumOfXX = \$FCAST->{SumXX};`
SumXY

Returns the sum of X * Y values.

` my \$SumOfXY = \$FCAST->{SumXY};`
AvgX

Returns the average of X values.

` my \$AvgX = \$FCAST->{AvgX};`
AvgY

Returns the average of Y values.

` my \$AvgY = \$FCAST->{AvgY};`
N

Return the number of X values.

` my \$N = \$FCAST->{N};`

# EXAMPLE

```   use Statistics::Forecast;

my @Y = (1,3,7,12);
my @X = (1,2,3,4);

my \$FCAST = Statistics::Forecast->new("My Forecast");

\$FCAST->{DataX} = \@X;
\$FCAST->{DataY} = \@Y;
\$FCAST->{NextX} = 8;
\$FCAST->calc;

print "The Forecast ", \$FCAST->{ForecastName};
print " has the forecast value: ", \$FCAST->{ForecastY}, "\n";```

# AUTHOR

This module was developed by Alex Falcao (alexjfalcao@hotmail.com)

# STATUS OF THE MODULE

This is the first version and calculates forecast value.

0.3