tssmooth_dexponential.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 dexponential}{right:dialog:  {bf:{dialog tssmooth_dexponential:tssmooth dexponential}}}
{hline}

{title:Title}

{p2colset 5 35 37 2}{...}
{p2col :{hi:[TS] tssmooth dexponential} {hline 2}}Double-exponential smoothing{p_end}
{p2colreset}{...}


{title:Syntax}

{p 8 20 2}
{cmd:tssmooth} {opt d:exponential} {dtype} {newvar} {cmd:=}
   {it:{help exp}} {ifin} [{cmd:,} 
   {it:options}]

{synoptset 15 tabbed}{...}
{synopthdr}
{synoptline}
{syntab:Main}
{synopt :{opt 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 values for
recursion{p_end}
{synopt :{opt s0(#1 #2)}}use {it:#1} and {it:#2} as initial values for
recursions{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}.


{title:Description}

{pstd}
{cmd:tssmooth dexponential} models the trend of a variable whose difference
between changes from the previous values is serially correlated.  More
precisely, it models a variable whose second-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
double-exponential smoothers; 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(#1 #2)} are mutually exclusive ways of specifying
the initial value for the recursion.

{pmore}
By default, initial values are obtained by fitting a linear regression with a
time trend using the first half of the observations in the dataset.

{pmore}
{opt samp0(#)} specifies that the first {it:#} be used in that regression.

{pmore}
{opt s0(#1 #2)} specifies that {it:#1} {it:#2} be used as initial values.

{phang}
{opt forecast(#)} specifies the number of periods for the out-of-sample
prediction.  {bind:0 {ul:<} {it:#} {ul:<} 500}.  The default is 0, which is
equivalent to not performing an out-of-sample forecast.


{title:Examples}

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

{psee}{cmd:. tssmooth dexponential sm2 = sales, forecast(4)}


{title:Also see}

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

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