[原创]gauss软件相关资源和学习资料，见跟贴

gauss_basic%20panel

gauss_basics

gauss_gmm

gauss_mle

 

168807.rar (355.65 KB)

2007-10-30 12:53:00 上传

[原创]强烈建议版主对gauss软件设置一个讨论帖，欢迎大家就学gauss软件遇到的问题帖出来，共同讨

不错，我要开始学学gauss了

贴一个gauss程序，请大家研究一下：

@ Written/Modified by: Junsoo Lee Disclaimer: This code is provided gratis without any guarantees or warrantees. Proprietary modifications of this code are not permitted. @ /* Im and Lee, Panel LM Unit Root Test with Level Shifts, WP, 2001 program: Panel_SP.txt Panel LM test using SP test with no breaks. See also, SP1.txt, panel_tw.txt (two breaks), panel_LS.txt (one break) Note: This program determines the optimal lag. */ @ ================================================================ @ out2 = "panel_sp.out"; "SP t-stat with the data-dependent choice of # lags "; "Also, panel test "; load crit[27,19] = c:\work\gauss\panelcri.dat; @ ================================================================ @ /* Options */ maxk = 8; @ # maximum augmentation lags allowed for @ n = 100; @ # of observations @ y = cumsumc(rndn(n,1)); @ Or, Read the dat file here. -> load y[n,1] = data.txt; @ n = 94; @ # of observations @ npanel = 19; @ # of panels @ @ ignored @ T1_end = .1; T2_end = .9; @ End points (10% of both ends are not considered) @ crit_t = 1.645; @ critical value of the t-stat for lag determination @ output file = ^out2 reset; format /rd/m1 4,0; "Date : ";; tt=date; tt[1:3]'; ""; "max p : " maxk; "# panels : " npanel; format /rd/m1 4,1; @ set up @ panel_t = zeros(npanel,1); panel_k = zeros(npanel,1); panel_b = zeros(npanel,1); @ ==== DATA ====================================================== @ load data[45,20] = c:\work\hyster\unemp2.txt; "Data: Unemp2.txt"; let name = Year Australia Austria Belgium Canada Denmark Finland France Germany Ireland Italy Japan Netherlands Norway Newzealand Spain Sweden Switzerland UK USA; jjj = 2; do while jjj <= 20; y = data[.,jjj]; @ Due to missing observations @ if jjj == 16; y = y[2:rows(data)]; endif; if jjj == 20; y = y[2:rows(data)]; endif; if jjj == 11; y = y[1:rows(data)-1]; endif; if jjj == 14; y = y[1:rows(data)-1]; endif; if jjj == 18; y = y[1:rows(data)-1]; endif; if jjj == 19; y = y[2:rows(data)-1]; endif; format /m1/rd 20,0 ; ""; ""; "|========> ";; "Series (not logged) : " $name[jjj,1]; ""; n = rows(y); format /m1/rd 5,0; "# of obs = " n; @ ================================================================ @ if cols(data) == npanel; mmm = jjj; fstcol = 0; elseif cols(data) == npanel+1; mmm = jjj-1; fstcol = 1; else; "Error in # of panels !!!"; stop; endif; format /m1/rd 6,4; "Panel # = ";; mmm; ""; /* End of Options */ @ imodel 1 = Crash model (dummy on the intercepts) 2 = Breaking trend (dummy on the trend) @ imodel=1; do while imodel <=1; @ once for each model for the panel test @ T = n; T1 = round(T1_end * rows(y)); T2 = round(T2_end * rows(y)); lag = 0; if T1 < maxk+2; T1 = maxk + 3; endif; lmestd1 = zeros(T,1); lmtd1 = zeros(T,1); lmlm1 = zeros(T,1); lmtk1 = zeros(T,1); lmoptk1 = zeros(T,1); T1 = 1; T2 = 1; ii = T1; Do while ii <= T2; output off; "*";; Estconf = ii; Estconf = 0; @ no break @ lmtk = zeros(maxk+1,1); lmlm = zeros(maxk+1,1); lmestd = zeros(maxk+1,1); lmtd = zeros(maxk+1,1); kk = 0; @ lag @ do while kk <= maxk; Estconf = ii; Estconf = 0; @ no break @ If imodel == 1; {lmtstat, lmed, lmtd0, lmres, lmbeta, lmtval, lmsig} = nLMk(y, EstConf,kk,0); Endif; If imodel == 2; {lmtstat, lmed, lmtd0, lmres, lmbeta, lmtval, lmsig} = nLMCk(y, EstConf,kk,0); Endif; lmestd[kk+1] = lmed; lmtd[kk+1] = lmtd0; lmlm[kk+1] = lmtstat; if kk > 0; lmtk[kk] = lmtval[kk+1]; endif; @ t-stat of the coeff. of the last augmented term @ kk = kk + 1; endo; jj = maxk; isw = 0; do while isw ne 1; if (abs(lmtk[jj]) > crit_t) or (jj == 0); lmoptk1[ii] = jj; isw = 1; endif; jj = jj - 1; endo; tt = lmoptk1[ii]+1; lmlm1[ii] = lmlm[tt]; ii = ii + 1; Endo; output on; lmo4 = minindc1(lmlm1[T1:T2]) + T1 - 1; optb = lmo4; optk = lmoptk1[optb]; optb = 0; @ no break @ format /rd/m1 10,4; ""; "-----------------------------------------"; ""; "Model (1=A, 2=C) = " imodel; If imodel == 1; {lmtstat, lmed, lmtd0, lmres, lmbeta, lmtval, lmsig} = nLMk(y, optb, optk, 0); Endif; If imodel == 2; {lmtstat, lmed, lmtd0, lmres, lmbeta, lmtval, lmsig} = nLMCk(y, optb, optk, 0); Endif; panel_t[mmm] = lmtstat; panel_k[mmm] = optk; panel_b[mmm] = optb; ""; "LM test statistic = " lmtstat; "Estimated break point = " optb; "Selected lag = " optk; ""; "Estimated coeff. of dummy var. = " lmed; "Its t-stat = " lmtd0; "Standard error .. = " lmsig; "Standardized dummy coeff = " lmed/lmsig; if imodel == 1; ""; "Coeff and t-stat"; "Z(t) = [S(t-1), (lags..omitted), 1, B(t)] "; endif; if imodel == 2; ""; "Coeff and t-stat"; "Z(t) = [S(t-1), (lags..omitted), 1, B(t), D(t)] "; endif; tt1 = lmbeta[1] | lmbeta[2+optk:rows(lmbeta)]; tt2 = lmtval[1] | lmtval[2+optk:rows(lmtval)]; tt3 = tt1 ~ tt2; tt3; ""; imodel = imodel + 1; endo; jjj=jjj+1; endo; @ Reading critical values @ @ row location @ if T < 10; row_n = 1; endif; if T > 10 and T < 25; row_n = T-10+1; endif; if T > 24 and T < 28; row_n = 16; endif; if T > 27 and T < 33; row_n = 17; endif; if T > 32 and T < 38; row_n = 18; endif; if T > 37 and T < 43; row_n = 19; endif; if T > 42 and T < 48; row_n = 20; endif; if T > 47 and T < 53; row_n = 21; endif; if T > 54 and T < 65; row_n = 22; endif; if T > 64 and T < 75; row_n = 23; endif; if T > 74 and T < 85; row_n = 24; endif; if T > 84 and T < 95; row_n = 25; endif; if T > 94 and T < 150; row_n = 26; endif; if T > 149; row_n = 27; endif; @ Calculating the panel LM test statistic @ ""; ""; "--------------------------------"; " PANEL LM statistic and summary "; "--------------------------------"; output file = ^out2 on; format /rd/m1 7,3; "";""; LM_t = panel_t; meanLM = meanc(LM_t); meanp = 0; varp = 0; mmm = 1; do while mmm <= npanel; @ column location @ if panel_k[mmm] > 8; optk = 8; else; optk = panel_k[mmm]; endif; ct1 = crit[row_n,2+2*optk]; ct2 = crit[row_n,3+2*optk]; ct = ct1 ~ ct2 ; ct'; meanp = meanp + crit[row_n,2+2*optk]; varp = varp + crit[row_n,3+2*optk]; mmm = mmm + 1; endo; meanp = meanp / npanel; varp = varp / npanel; panel_LM = sqrt(npanel) * (meanLM - meanp) / sqrt(varp); "Panel LM test statistic = " panel_LM; ""; outt = seqa(1,1,npanel)~panel_t~panel_k~panel_b; "Individual (i) LM statistic (ii) opt p and (iii) opt break point"; outt; ""; t1 = seqa(1,1,19); t1'; $name[2:20]'; /* Format: {lmtstat, lmed, lmtd0, lmres, lmbeta, lmtval, lmsig} = nLMCk(y, EstConf,kk,0); Input: y = series Estconf = position of the structural break kk = # of augmentation lags q = # of truncation lags (ignore here) Output: lmtstat = ADF t-statistic lmd = estimated coefficients of break dummies lmtd0 = t-stat for coefficients of break dummies lmres = residuals lmbeta = all estimated coefficients lmtval = t-stat of estimated coefficients lmsig = standard error of regression */ proc (7) = nLMk(y, config, lag, q); local lr, res, lhat, alpha, za, zt, nobs, dy, rho; local sse, tau, ratios, i, n, z, dz, pos, st, du, s1, ind, tt, temp, sai; local RR, tdel, whvar, nwvar, temp2, dt, estd, td, ch, k, stat; nobs = rows(y); if (config == 0); RR = 0; z = seqa(1,1,nobs); dz = ones(nobs-1,1); endif; if (config ne 0); RR = rows(config); pos = config[1]; du = zeros(pos,1) | ones(nobs-pos,1); i=2; do while i <= RR; pos = config; temp = zeros(pos,1) | ones(nobs-pos,1); du = du ~ temp; i = i + 1; endo; z = seqa(1,1,nobs) ~ du; dz = diff(z,1); endif; dy = diff(y,1); tdel = dy / dz; sai = y[1] - z[1,.]*tdel; st = y - sai - z*tdel; s1 = st[1:rows(st)-1,1]; ind = s1; ch = diff(st,1); k = 0 ; If (lag > 0) ; do until k >= lag ; k = k + 1 ; ind = ind ~ lagn(ch,k) ; endo ; Endif ; dy = trimr(dy,k,0); ind = trimr(ind,k,0); dz = trimr(dz,k,0); ind = ind ~ dz; alpha = dy / ind; rho = nobs * alpha[1]; res = dy - ind*alpha; sse = res'res/(rows(res)); tt = sqrt(sse*inv(ind'ind)); tau = alpha[1] ./ tt[1,1]; @WhVar = WhiteEst(res,q); NWVar = NewWEST(res,q);@ @LEE@ stat = tau; if q > 0; lr = lrvar(res,q); ratios = sse / lr; Za = rho / ratios; Zt = tau / sqrt(ratios); stat = zt; endif; estd = alpha[rows(alpha)]; td = estd ./ tt[rows(alpha),rows(alpha)]; retp(stat, estd, td, res, alpha, alpha./diag(tt), sqrt(sse)); endp ; /* Model C */ proc (7) = nLMCk(y, config, lag, q); local lr, res, lhat, alpha, za, zt, nobs, dy, rho; local sse, tau, ratios, i, n, z, dz, pos, st, du, s1, ind, tt, temp, sai; local RR, tdel, whvar, nwvar, temp2, dt, estd, td, ch, k, stat; nobs = rows(y); if (config == 0); RR = 0; z = seqa(1,1,nobs); dz = ones(nobs-1,1); endif; if (config ne 0); RR = rows(config); pos = config[1]; du = zeros(pos,1) | ones(nobs-pos,1); dt = zeros(pos,1) | seqa(1,1,nobs-pos); i=2; do while i <= RR; pos = config; temp = zeros(pos,1) | ones(nobs-pos,1); temp2 = zeros(pos,1) | seqa(1,1,nobs-pos); du = du ~ temp; dt = dt ~ temp2; i = i + 1; endo; z = seqa(1,1,nobs) ~ du ~ dt; dz = diff(z,1); endif; dy = diff(y,1); tdel = dy / dz; sai = y[1] - z[1,.]*tdel; st = y - sai - z*tdel; s1 = st[1:rows(st)-1,1]; ind = s1; ch = diff(st,1); k = 0 ; If (lag > 0) ; do until k >= lag ; k = k + 1 ; ind = ind ~ lagn(ch,k) ; endo ; Endif ; dy = trimr(dy,k,0); ind = trimr(ind,k,0); dz = trimr(dz,k,0); ind = ind ~ dz; alpha = dy / ind; rho = nobs * alpha[1]; res = dy - ind*alpha; sse = res'res/(rows(res)); tt = sqrt(sse*inv(ind'ind)); tau = alpha[1] ./ tt[1,1]; @WhVar = WhiteEst(res,q); NWVar = NewWEST(res,q);@ @LEE@ stat = tau; if q > 0; lr = lrvar(res,q); ratios = sse / lr; Za = rho / ratios; Zt = tau / sqrt(ratios); stat = zt; endif; estd = alpha[rows(alpha)]; td = estd ./ tt[rows(alpha),rows(alpha)]; retp(stat, estd, td, res, alpha, alpha./diag(tt), sqrt(sse)); endp ; proc lagn(x,n); local y; y = shiftr(x', n, (miss(0, 0))'); retp(y'); endp; proc diff(x,k) ; if ( k == 0) ; retp(x) ; endif ; retp(trimr(x,k,0)-trimr(lagn(x,k),k,0)) ; endp ; proc ptrend(p,nobs) ; local data, t, u, m, timep, it, iit, xmat, invx, beta, resid ; u = ones(nobs,1) ; if p > 0 ; timep = zeros(nobs,p) ; t = seqa(1,1,nobs); m = 1 ; do while m <= p ; timep[.,m] = t^m ; m = m + 1 ; endo ; xmat = u~timep ; else ; xmat = u ; endif ; retp(xmat) ; endp ; proc (1) = minindc1(x); local d,m,i,minx; m = 1; d = x[1]; i=1; do while i <=rows(x); if x < d; d = x; endif; i=i+1; endo; i=2; do while i <= rows(x); if d == x; m = i; goto stops; endif; i = i + 1; endo; stops: retp(m); endp; 

169733.pdf (498.43 KB)

2007-11-3 08:44:00 上传

[原创]强烈建议版主对gauss软件设置一个讨论帖，欢迎大家就学gauss软件遇到的问题帖出来，共同讨

这是相对应的文章。

老实说，我看不懂这个程序，总觉得有问题。研究gauss的同学都可以来看一看。

我不知道你在哪些方面看不懂？lee给的这几个程序，不是很好用，特别是用自己的数据估计的时候，总会出现问题，估计的结果与经验判断出的有差错。

[此贴子已经被作者于2007-11-3 17:51:42编辑过]

是啊，这个程序肯定是不能直接用的，现在的问题是我根本就不懂他的这个思想！跟他本人的论文完全对不上嘛。

xuelida你看他的LM统计量是如何算出来的？在他的程序里面？我是没看明白。

If imodel == 1;
  {lmtstat, lmed, lmtd0, lmres, lmbeta, lmtval, lmsig} =nLMk(y, optb, optk, 0);
Endif;
If imodel == 2;
 {lmtstat, lmed, lmtd0, lmres, lmbeta, lmtval, lmsig} = nLMCk(y, optb, optk, 0);
Endif;

上面两个是lm估计

lm估计量应该是tau    = alpha[1] ./ tt[1,1];

这个是调用的估计程序proc (7) = nLMk(y, config, lag, q);

[此贴子已经被作者于2007-11-5 19:36:59编辑过]

(1)** The regressors are now different across individual data sets.
** That is, regressors are stochastic.
** The errors are different across different data sets
** Errors are normal

(2)** ** The regressors are now different across individual data sets.
** That is, regressors are stochastic.
** The errors are different across different data sets
** Errors are not normal:  chi-square(2) - 2

(3)** ** The regressors are lagged dependent variables.
** That is, regressors are stochastic.
** The errors are different across different data sets
** Errors are normal:

(4)** The regressors are lagged dependent variables.
** That is, regressors are stochastic.
** The errors are different across different data sets.
** Errors are non-normal: Chi-square(2)-2

170737.rar (3.69 KB, 需要: 2 个论坛币)

2007-11-5 19:26:00 上传

[原创]gauss软件讨论帖，欢迎大家就学gauss软件遇到的问题帖出来，共同讨论。
需要: 2 个论坛币  [购买]

[此贴子已经被作者于2007-11-5 19:37:23编辑过]