jackknife.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}
{* 22mar2005}{...}
{cmd:help jackknife}{...}
{right:dialog:  {bf:{dialog jackknife}}{space 15}}
{right:also see:  {help jackknife postestimation}}
{hline}

{title:Title}

{p2colset 5 22 24 2}{...}
{p2col :{hi:[R] jackknife} {hline 2}}Jackknife estimation{p_end}
{p2colreset}{...}


{title:Syntax}

{p 8 18 2}
{cmd:jackknife}
	{it:{help exp_list}}
	[{cmd:,}
		{it:options}
		{it:{help eform_option}}
	] {cmd::} {it:command}


{synoptset 25 tabbed}{...}
{synopthdr}
{synoptline}
{syntab :Main}
{synopt :{opt e:class}}number of observations used is stored in {cmd:e(N)}{p_end}
{synopt :{opt r:class}}number of observations used is stored in {cmd:r(N)}{p_end}
{synopt :{opth n(exp)}}specify
	{it:exp} that evaluates to the number of observations used {p_end}

{syntab :Options}
{synopt :{opth cl:uster(varlist)}}variables identifying sample clusters{p_end}
{synopt :{opth id:cluster(newvar)}}create new cluster ID variable{p_end}
{synopt :{help prefix_saving_option:{bf:saving(}{it:filename}{bf:, ...)}}}save
	results to {it:filename}; save statistics in double precision; save
	results to {it:filename} every {it:#} replications{p_end}
{synopt :{opt keep}}keep pseudovalues{p_end}
{synopt :{opt mse}}use MSE formula for variance estimate{p_end}

{syntab :Reporting}
{synopt :{opt l:evel(#)}}set confidence level; default is {cmd:level(95)}{p_end}
{synopt :{opt notable}}suppress table of results{p_end}
{synopt :{opt noh:eader}}suppress the table header{p_end}
{synopt :{opt nol:egend}}suppress the table legend{p_end}
{synopt :{opt v:erbose}}display the full table legend{p_end}
{synopt :{opt nodots}}suppress the replication dots{p_end}
{synopt :{opt noi:sily}}display any output from {it:command}{p_end}
{synopt :{opt tr:ace}}trace the {it:command}{p_end}
{synopt :{opt ti:tle(text)}}use {it:text} as title for jackknife results{p_end}

{syntab :Advanced}
{synopt :{opt nodrop}}do not drop observations{p_end}
{synopt :{opth reject(exp)}}identify invalid results{p_end}

{p2coldent :+ {it:eform_option}}display coefficient table in
exponentiated form{p_end}
{synoptline}
{p2colreset}{...}
{p 4 6 2}
+ {it:eform_option} does not appear in the dialog box.{p_end}
{p 4 6 2}
{opt svy} may be used with {opt jackknife}; see {helpb "svy jackknife"}.{p_end}
{p 4 6 2}
{opt fweight}s, {opt pweight}s, and {opt iweight}s are allowed in
{it:command}; see {help weight}.{p_end}
{p 4 6 2}
See {help jackknife postestimation} for features available after estimation.{p_end}


{title:Description}

{pstd}
{opt jackknife} performs jackknife estimation.  Typing

{pin}
{cmd:. jackknife} {it:exp_list}{cmd::} {it:command}

{pstd}
executes {it:command} once for each observation in the dataset, leaving the
associated observation out of the calculations that make up {it:exp_list}.

{pstd}
{it:command} defines the statistical command to be executed.
Most Stata commands and user-written programs can be used with
{opt jackknife}, as long as they follow {help language:standard Stata syntax}
and allow the {it:{help if}} qualifier.
The {opt by} prefix may not be part of {it:command}.

{pstd}
{it:exp_list} specifies the statistics to be collected from the execution of
{it:command}.  If {it:command} changes the contents in {cmd:e(b)},
{it:exp_list} is optional and defaults to {cmd:_b}.

{pstd}
Many estimation commands allow the {cmd:vce(jackknife)} option.  For those
commands, we recommend using {cmd:vce(jackknife)} over {cmd:jackknife} since
the estimation command already handles clustering and other model-specific 
details for you.  The {cmd:jackknife} prefix command is intended for use
with nonestimation commands, such as {cmd:summarize}, user-written commands, 
or functions of coefficients.

{pstd}
{cmd:jknife} is a synonym for {cmd:jackknife}.


{title:Options}

{dlgtab:Main}

{phang}
{opt eclass}, {opt rclass}, and {opth n(exp)} specify where
{it:command} saves the number of observations on which it based the calculated
results.  We strongly advised you to specify one of these options.

{pmore}
{opt eclass} specifies that {it:command} save the number of observations
in {hi:e(N)}.

{pmore}
{opt rclass} specifies that {it:command} save the number of observations
in {hi:r(N)}.

{pmore}
{opt n(exp)} specifies an expression
that evaluates to the number of observations used.  Specifying
{cmd:n(r(N))} is the equivalent to specifying option {opt rclass}.  Specifying
{cmd:n(e(N))} is the equivalent to specifying option {opt eclass}.  If
{it:command} saved the number of observations in {cmd:r(N1)},
specify {cmd:n(r(N1))}.

{pmore}
If you don't specify any options, {opt jackknife} will assume
{opt eclass} or
{opt rclass}, depending upon which of {hi:e(N)} and {hi:r(N)} is not missing
(in that order).
If both {hi:e(N)} and {hi:r(N)} are missing, {opt jackknife} assumes that all
observations in the dataset contribute to the calculated result.  If
that assumption is incorrect, the reported standard errors
will be incorrect.  For instance, say that you specify

{center:{cmd:. jackknife coef=_b[x2]: myreg y x1 x2 x3}}

{pmore}
where {opt myreg} uses {cmd:e(n)} instead of {cmd:e(N)} to identify the number
of observations used in calculations.  Further assume that observation 42 in
the dataset has {opt x3} equal to missing.  The 42nd observation plays no role
in obtaining the estimates, but {opt jackknife} has no way of knowing that and
will use the wrong {it:N}.  If, on the other hand, you specify

{center:{cmd:. jackknife coef=_b[x2], n(e(n)): myreg y x1 x2 x3}}

{pmore}
{opt jackknife} will notice that observation 42 plays no role.  Option
{cmd:n(e(n))} is specified because {opt myreg} is an estimation command but it
saves the number of observations used in {cmd:e(n)} (instead of the standard
{cmd:e(N)}). When {opt jackknife} runs the regression omitting the 42nd
observation, {opt jackknife} will observe that {cmd:e(n)} has the same value
as when {opt jackknife} previously ran the regression using all the
observations.  Thus {opt jackknife} will know that {opt myreg} did not use the
observation.

{dlgtab:Options}

{phang}
{opth cluster(varlist)} specifies the variables identifying
sample clusters.  If {opt cluster()} is specified, one cluster is
left out of each call to {it:command}, instead of one observation.

{phang}
{opth idcluster(newvar)} creates a new variable containing a
unique integer identifier for each resampled cluster, starting at {opt 1} and
leading up to the number of clusters.  This option may only be specified when
the {opt cluster()} option is specified.
{opt idcluster()} helps identify the cluster to which a
pseudovalue belongs.

INCLUDE help prefix_saving_option

{pmore}
See {it:{help prefix_saving_option}} for details about {it:suboptions}.

{phang2}
{opt replace} indicates that {it:filename} be overwritten, if it exists.  This
option is not shown on the dialog box.

{phang}
{opt keep} specifies that new variables are to be added to the dataset
containing the pseudovalues of the requested statistics.  See 
{bind:{bf:[R] jackknife}} for details.  When the {opt cluster()} option is
specified, each cluster is given at most one nonmissing pseudovalue.  This
option implies the {opt nodrop} option.

{phang}
{opt mse} specifies that {opt jackknife} compute the variance using deviations
of the replicates from the observed value of the statistics based on the
entire dataset.  By default, {opt jackknife} computes the variance using
deviations of the pseudovalues from their mean.

{dlgtab:Reporting}

{phang}
{opt level(#)}; see {help estimation options}.

{phang}
{opt notable} suppresses the display of the table of results.

{phang}
{opt noheader} suppresses display of the table header.
This option implies {opt nolegend}.

{phang}
{opt nolegend} suppresses display of the table legend.  The table
legend identifies the rows of the table with the expressions they represent.

{phang}
{opt verbose} requests that the full table legend be displayed.  By default,
coefficients and standard errors are not displayed.

{phang}
{opt nodots} suppresses display of the replication dots. By
default, a single dot character is printed for each successful replication.
A single red `x' is displayed if {it:command} returns an error or if
one of the values in {it:exp_list} is missing.

{phang}
{opt noisily} requests that any output from {it:command} be displayed.
This option implies the {opt nodots} option.

{phang}
{opt trace} causes a trace of the execution of {it:command} to be displayed.
This option implies the {opt noisily} option.

{phang}
{opt title(text)} specifies a title to be displayed above the
table of jackknife results; the default title is {opt Jackknife results} or what is 
produced in {cmd:e(title)} by an estimation command.

{dlgtab:Advanced}

{phang}
{opt nodrop} prevents observations outside {cmd:e(sample)} and the {it:if}
and {it:in} qualifiers from being dropped before the data is resampled.

{phang}
{opth reject(exp)} identifies an expression that indicates when results should
be rejected.  When {it:exp} is true, the resulting values are reset to missing
values.

{pstd}
The following option is available with {opt jackknife} but is not
shown in the dialog box:

{phang}
{it:eform_option} causes the coefficient table to be displayed in
exponentiated form; see {it:{help eform_option}}.  {it:command} determines
which {it:eform_option} is allowed ({opt eform(string)} and {opt eform} are
always allowed).


{title:Examples}

{phang}
{cmd:. jackknife sd=r(sd), rclass keep: summarize x}
{p_end}

{phang}
{cmd:. jackknife sd=r(sd), rclass keep: summarize mpg}
{p_end}

{phang}
{cmd:. jackknife sd=r(sd) skew=r(skewness), rclass: summarize mpg, detail}
{p_end}

{phang}
{cmd:. jackknife _b _se, eclass: reg mpg weight trunk}
{p_end}


{title:Also see}

{psee}
Manual:  {hi:[R] jackknife}

{psee}
Online:  {help jackknife postestimation};{break}
{helpb bootstrap},
{helpb permute},
{helpb postfile},
{helpb simulate},
{helpb statsby};
{helpb "svy jackknife"}
{p_end}