tssmooth_hwinters.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:tssmooth hwinters}{right:dialog:  {bf:{dialog tssmooth_hwinters:tssmooth hwinters}}}
{hline}

{title:Title}

{p2colset 5 31 33 2}{...}
{p2col :{hi:[TS] tssmooth hwinters} {hline 2}}Holt-Winters nonseasonal smoothing{p_end}
{p2colreset}{...}


{title:Syntax}

{p 8 27 2}
{cmd:tssmooth} {opt h:winters} {dtype} {newvar} {cmd:=} {it:{help exp}} 
   {ifin} [{cmd:,} {it:options}]

{synoptset tabbed}{...}
{synopthdr}
{synoptline}
{syntab:Main}
{synopt :{cmd:replace}}replace {newvar} if it already exists{p_end}
{synopt :{opt p:arms(#a #b)}}use {it:#a} and {it:#b} as smoothing parameters{p_end}
{synopt :{opt sa:mp0(#)}}use {it:#} observations to obtain initial values for 
  recursion{p_end}
{synopt :{cmd:s0(}{it:#}cons {it:#}lt{cmd:)}}use {it:#}cons and {it:#}lt as initial values for recursion{p_end}
{synopt :{opt f:orecast(#)}}use {it:#} periods for the out-of-sample
  prediction{p_end}

{syntab:Options}
{synopt :{opt d:iff}}alternative initial-value specification; see
          {help tssmooth hwinters##diff:Options}{p_end}

{syntab:Max options}
{synopt :{it:{help tssmooth hwinters##maximize_options:maximize_options}}}control the maximization process; seldom used
{p_end}
{synopt :{opt fr:om(#a #b)}}report starting values for the parameters{p_end}
{synoptline}
{p2colreset}{...}
{p 4 6 2}You must {helpb tsset} your data before using 
{cmd:tssmooth hwinters}.{p_end}
{p 4 6 2}{it:{help exp}} may contain time-series operators; see 
{help tsvarlist}.


{title:Description}

{pstd}
{cmd:tssmooth hwinters} is used in smoothing or forecasting a series that can
be modeled as a linear trend in which the intercept and the coefficient on
time vary over time.


{title:Options}

{dlgtab:Main}

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

{phang}
{opt parms(#a #b)}, 0 {ul:<} {it:#a} {ul:<} 1 and 
{bind:0 {ul:<} {it:#b} {ul:<} 1}, specifies the parameters.  If {opt parms()}
is not specified, the values are chosen by an iterative process to minimize
the in-sample sum-of-squared prediction errors.

{pmore}
If you experience difficulty converging (many iterations and "not concave"
messages), try using {opt from()} to provide better starting values.

{phang}
{opt samp0(#)} and {cmd:s0(}{it:#}cons {it:#}lt{cmd:)} specify how the initial
values {it:#}cons and {it:#}lt for the recursion are obtained.

{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:#} observations be used in that
regression.

{pmore}
{cmd:s0(}{it:#}cons {it:#}lt{cmd:)} specifies that {it:#}cons and {it:#}lt
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.


{dlgtab:Options}

{phang}
{marker diff}{...}
{opt diff} specifies the linear term is obtained by averaging the
first-difference of {it:exp_t} and the intercept is obtained as the difference
of {it:exp} in the first observation and the mean of {opt D}.{it:exp_t}.

{pmore}
If option {opt diff} is not specified, a linear regression of {it:exp_t} on a
constant and {it:t} is fit.

{dlgtab:Max options}

{phang}
{marker maximize_options}{...}
{it:maximize_options} controls the process for solving for the optimal alpha
and beta when {opt parms()} is not specified.

{pmore}
{it:maximize_options:} {opt nodif:ficult}, {opt tech:nique(algorithm_spec)},
{opt iter:ate(#)}, [{cmd:{ul:no}}]{opt lo:g}, {opt tr:ace},
{opt grad:ient}, {opt showstep}, {opt hess:ian}, {opt shownr:tolerance},
{opt tol:erance(#)}, {opt ltol:erance(#)}, 
{opt gtol:erance(#)}, {opt nrtol:erance(#)}, {opt nonrtol:erance}, see 
{help maximize}.  These options are seldom used.

{pmore}
{opt from(#a #b)}, 0 < {it:#a} < 1 and 0 < {it:#b} < 1,
specifies starting values from which the optimal values of 
alpha and beta will be obtained.  If {opt from()} is not specified, 
{cmd:from(.5 .5)} is used.


{title:Examples}

{psee}{cmd:. tssmooth hwinters hw1 = sales, parms(.3 .2)}

{psee}{cmd:. tssmooth hwinters hw2 = sales, forecast(4)}


{title:Also see}

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

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