tssmooth_exponential.hlp

是一个经济学管理应用软件 很难找的 但是经济学学生又必须用到

{smcl}
{* 08mar2005}{...}
{cmd:help tssmooth exponential}{right:dialog:  {bf:{dialog tssmooth_exponential:tssmooth exponential}}}
{hline}

{title:Title}

{p2colset 5 34 36 2}{...}
{p2col :{hi:[TS] tssmooth exponential} {hline 2}}Single-exponential smoothing{p_end}
{p2colreset}{...}


{title:Syntax}

{p 8 29 2}
{cmd:tssmooth} {opt e:xponential} {dtype} {newvar} {cmd:=} {it:{help exp}}
   {ifin} [{cmd:,} {it:options}]

{synoptset 15 tabbed}{...}
{synopthdr}
{synoptline}
{syntab:Main}
{synopt :{cmd:replace}}replace {newvar} if it already exists{p_end}
{synopt :{opt p:arms(#a)}}use {it:#a} as smoothing parameter{p_end}
{synopt :{opt sa:mp0(#)}}use {it:#} observations to obtain initial value for
   recursion{p_end}
{synopt :{opt s0(#)}}use {it:#} as initial value for recursion{p_end}
{synopt :{opt f:orecast(#)}}use {it:#} periods for the out-of-sample 
   forecast{p_end}
{synoptline}
{p2colreset}{...}
{p 4 6 2}You must {helpb tsset} your data before using {cmd:tssmooth}.{p_end}
{p 4 6 2}{it:{help exp}} may contain time-series operators; see 
   {help tsvarlist}.{p_end}


{title:Description}

{pstd}
{cmd:tssmooth exponential} models the trend of a variable whose change from
the previous value is serially correlated.  More precisely, it models a
variable whose first-difference follows a low-order, moving-average process.


{title:Options}

{dlgtab:Main}

{phang}
{opt replace} replaces {newvar} if it already exists.

{phang}
{opt parms(#a)} specifies the parameter alpha for the exponential smoother; 0
< {it:#a} < 1.  If {opt parms(#a)} is not specified, the smoothing parameter
is chosen to minimize the in-sample sum-of-squared forecast errors.

{phang}
{opt samp0(#)} and {opt s0(#)} are mutually exclusive ways of specifying
the initial value for the recursion.

{pmore}
{opt samp0(#)} specifies that the initial value be obtained by calculating the
mean over the first {it:#} observations of the sample.

{pmore}
{opt s0(#)} specifies the initial value to be used.

{pmore}
If neither option is specified, the default is to use the mean calculated over
the first half of the sample.

{phang}
{opt forecast(#)} gives the number of observations for the out-of-sample
prediction, where {bind:0 {ul:<} {it:#} {ul:<} 500}.  The default is 0
and is equivalent to not forecasting out-of-sample.


{title:Examples}

{psee}{cmd:. tssmooth exponential sm1 = sales, parms(.3)}

{psee}{cmd:. tssmooth exponential sm2 = sales}


{title:Also see}

{psee}
Manual:  {bf:[TS] tssmooth exponential}

{psee}
Online:  {helpb arima}, {helpb egen}, {helpb generate},
{helpb tsset}, {helpb tssmooth dexponential}, {helpb tssmooth hwinters}, 
{helpb tssmooth ma}, {helpb tssmooth nl}, {helpb tssmooth shwinters}{p_end}