The LinearFilter function applies linear filter to a set of observations. By default, convolution method is used:

`X'`[i] = Sum(X[i+1-j]*Y[j], j = 1..m);

where m is the size of the filter. For  the set of initial values will be used. By default, X is padded on the left with  zeros. Option initial can be used to specify the initial values.

Recursive filter is defined as follows:

`X'`[i] = X[i]*Y[1]+Sum(`X'`[i+1-j]*Y[j], j = 2..m);

The first parameter X is a single data sample - given as a Vector or list. Each value represents an individual observation.

The second parameter Y is the filter - given as a Vector or list. Each value represents a filter coefficient.

The options argument can contain one or more of the options shown below.

ignore=truefalse -- This option is used to specify how to handle non-numeric data. If ignore is set to true all non-numeric items in data will be ignored. Missing values are allowed in the data set but not in the filter.

initial=deduce, or Vector -- This option specifies the initial values in reverse order. The default is a set of  zeros.

recursive=truefalse -- If this option is set to true then recursive filter will be used.