Commit a5ed8187 authored by Houtan Bastani's avatar Houtan Bastani
Browse files

SWZ: remove extra whitespace

parent 248cc388
......@@ -742,11 +742,11 @@ int ReadBaseTransitionMatricesFlat_SV(FILE *f_in, TMarkovStateVariable *sv)
FreeMatrix(Q);
return 0;
}
// Scale the columns of Q - loose requirement on sumation to one
for (j=sv->nbasestates-1; j >= 0; j--)
{
for (sum=0.0, i=sv->nbasestates-1; i >= 0; i--)
for (sum=0.0, i=sv->nbasestates-1; i >= 0; i--)
if (ElementM(Q,i,j) < 0.0)
{
FreeMatrix(Q);
......@@ -761,7 +761,7 @@ int ReadBaseTransitionMatricesFlat_SV(FILE *f_in, TMarkovStateVariable *sv)
dw_UserError("Transition matrix columns must sum to one.");
return 0;
}
for (sum=1.0/sum, i=sv->nbasestates-1; i >= 0; i--)
for (sum=1.0/sum, i=sv->nbasestates-1; i >= 0; i--)
ElementM(Q,i,j)*=sum;
}
......
......@@ -2398,8 +2398,8 @@ void Update_lambda_psi_from_bplus(T_VAR_Parameters *p)
forecast : horizon x nvars matrix or null pointer
horizon : positive integer - forecast horizon
initial : initial value of predetermined variables.
shocks : array of length horizon of shocks or null pointer. If null
pointer, then the shocks are all zero. Each vector is of length
shocks : array of length horizon of shocks or null pointer. If null
pointer, then the shocks are all zero. Each vector is of length
nvar.
S : array of length horizon. S[t] is the state at time T+1+t.
model : pointer to valid TStateModel structure.
......@@ -2408,7 +2408,7 @@ void Update_lambda_psi_from_bplus(T_VAR_Parameters *p)
Computes forecast
Returns:
The matrix forecast upon success and null upon failure. If forecast is
The matrix forecast upon success and null upon failure. If forecast is
null, then it created.
*/
TMatrix forecast_base(TMatrix forecast, int horizon, TVector initial, TVector *shocks, int *S, TStateModel *model)
......@@ -2455,7 +2455,7 @@ TMatrix forecast_base(TMatrix forecast, int horizon, TVector initial, TVector *s
}
/*
For 1 <= k < h, y[k][i] is null if the ith coordinate of y(t0+1+k) is
For 1 <= k < h, y[k][i] is null if the ith coordinate of y(t0+1+k) is
unrestricted and is its value otherwise. In general, t0 is the last index for
which we have full information. It must be the case that t0 <= nobs.
*/
......@@ -2570,7 +2570,7 @@ TMatrix forecast_base(TMatrix forecast, int horizon, TVector initial, TVector *s
/* } */
/*
*/
/* TVector* dw_state_space_mean_unconditional_forecast(TVector *F, int h, int t0, TStateModel *model) */
/* { */
......@@ -3580,7 +3580,7 @@ TMatrix MakeA0(TMatrix A0, int s, T_VAR_Parameters *p)
/*
Assumes:
A0 : Matrix array of length n_states or null pointer. A0[s] is either
A0 : Matrix array of length n_states or null pointer. A0[s] is either
p->nvars x p->nvars matrix or null pointer
*/
TMatrix* MakeA0_All(TMatrix *A0, T_VAR_Parameters *p)
......@@ -3634,7 +3634,7 @@ TMatrix MakeAplus(TMatrix Aplus, int k, T_VAR_Parameters *p)
/*
Assumes:
Aplus : Matrix array of length n_states or null pointer. Aplus[s] is either
Aplus : Matrix array of length n_states or null pointer. Aplus[s] is either
p->npre x p->nvars matrix or null pointer
*/
TMatrix* MakeAplus_All(TMatrix *Aplus, T_VAR_Parameters *p)
......@@ -3684,7 +3684,7 @@ TMatrix MakeZeta(TMatrix Zeta, int k, T_VAR_Parameters *p)
/*
Assumes:
Zeta : Matrix array of length n_states or null pointer. Zeta[s] is either
Zeta : Matrix array of length n_states or null pointer. Zeta[s] is either
p->vars x p->nvars matrix or null pointer
*/
TMatrix* MakeZeta_All(TMatrix *Zeta, T_VAR_Parameters *p)
......
......@@ -20,7 +20,7 @@
model : point to valid TStateModel structure
Results:
Computes and prints to the file f_out the requested percentiles for forecasts
Computes and prints to the file f_out the requested percentiles for forecasts
of the observables.
Returns:
......@@ -84,7 +84,7 @@ int forecast_percentile(FILE *f_out, TVector percentiles, int draws, FILE *poste
{
// Draw time T regime
m=DrawDiscrete(init_prob);
// Draw regimes from time T+1 through T+h inclusive
for (j=0; j < h; j++)
{
......@@ -138,7 +138,7 @@ ERROR_EXIT:
model : point to valid TStateModel/T_MSStateSpace structure
Results:
Computes and prints to the file f_out the requested percentiles for forecasts
Computes and prints to the file f_out the requested percentiles for forecasts
of the observables.
Returns:
......@@ -146,10 +146,10 @@ ERROR_EXIT:
Notes:
The regime at time T is drawn from the filtered probabilities at time t, and
is set to s there after.
is set to s there after.
*/
int forecast_percentile_regime(FILE *f_out, TVector percentiles, int draws,
int forecast_percentile_regime(FILE *f_out, TVector percentiles, int draws,
FILE *posterior_file, int s, int T, int h, TStateModel *model)
{
T_VAR_Parameters *p;
......@@ -238,54 +238,54 @@ ERROR_EXIT:
/*
Attempt to set up model from command line. Command line options are the
Attempt to set up model from command line. Command line options are the
following
-ft <filename tag>
If this argument exists, then the following is attempted:
specification file name = est_final_<tag>.dat
output file name = ir_<tag>_regime_<k>.dat
parameters file name = est_final_<tag>.dat
parameters file name = est_final_<tag>.dat
header = "Posterior mode: "
-fs <filename>
If this argument exists, then the specification file name is <filename>.
If this argument exists, then the specification file name is <filename>.
The argument -fs takes precedence over -ft.
-fp <filename>
If this argument exists, then the parameters file name is <filename>. The
argument -fp takes precedence over -ft. The default value is the filename
If this argument exists, then the parameters file name is <filename>. The
argument -fp takes precedence over -ft. The default value is the filename
associated with the argument -fs.
-ph <header>
If this argument exists, then the header for the parameters file is
If this argument exists, then the header for the parameters file is
<header>. The default value is "Posterior mode: ".
-horizon <integer>
If this argument exists, then the horizon of the impulse responses is given
by the passed integer. The default value is 12.
-error_bands
-error_bands
Output error bands. (default = off - only median is computed)
-percentiles n p_1 p_2 ... p_n
Percentiles to compute. The first parameter after percentiles must be the
number of percentiles and the following values are the actual percentiles.
Percentiles to compute. The first parameter after percentiles must be the
number of percentiles and the following values are the actual percentiles.
default = 3 0.16 0.50 0.84 if error_bands flag is set
= 1 0.50 otherwise
-parameter_uncertainty
-parameter_uncertainty
Apply parameter uncertainty when computing error bands.
-shocks_per_parameter <integer>
Number of shocks and regime paths to draw for each parameter draw. The
-shocks_per_parameter <integer>
Number of shocks and regime paths to draw for each parameter draw. The
default value is 1 if parameter_uncertainty is set and 10,000 otherwise.
-thin
Thinning factor. Only 1/thin of the draws in posterior draws file are
-thin
Thinning factor. Only 1/thin of the draws in posterior draws file are
used. The default value is 1.
-regimes
-regimes
Produces forecasts as if each regime were permanent. (default = off)
-regime <integer>
......@@ -328,7 +328,7 @@ int main(int nargs, char **args)
// parameter filename
if (!parm)
sprintf(parm=(char*)malloc(strlen(fmt) + strlen(tag) - 1),fmt,tag);
}
}
// horizon
horizon=dw_ParseInteger_String(nargs,args,"horizon",12);
......@@ -344,7 +344,7 @@ int main(int nargs, char **args)
" -horizon : horizon for the forecast (12)\n"
);
exit(1);
}
}
if (!parm)
strcpy(parm=(char*)malloc(strlen(spec)+1),spec);
......@@ -364,7 +364,7 @@ int main(int nargs, char **args)
free(head);
free(parm);
//============================= Compute forecasts =============================
//============================= Compute forecasts =============================
// Mean forecast
/* if (dw_FindArgument_String(nargs,args,"mean") != -1) */
......
......@@ -12,7 +12,7 @@ static void AddObservationFixed(PRECISION x, int *low, int *h, int *high, PRECIS
static PRECISION Cumulative(PRECISION level, int low, int *h, PRECISION min, PRECISION max, int intervals, int sample_size);
static PRECISION Percentile(PRECISION percentile, int low, int *h, PRECISION min, PRECISION max, int intervals, int sample_size);
static TMatrix MakeHistogram(int low, int *h, PRECISION min, PRECISION max,int intervals, int sample_size,
static TMatrix MakeHistogram(int low, int *h, PRECISION min, PRECISION max,int intervals, int sample_size,
PRECISION min_out, PRECISION max_out, int bins);
static TMatrix MakeHistogramAuto(int low, int *h, int high, PRECISION min, PRECISION max, int intervals, int sample_size, int bins);
......@@ -53,7 +53,7 @@ TMatrixHistogram *CreateMatrixHistogram(int rows, int cols, int intervals, int t
if (!(h->high=(int**)malloc(rows*sizeof(int*)))) dw_Error(MEM_ERR);
for (i=rows-1; i >= 0; i--)
if (!(h->high[i]=(int*)malloc(cols*sizeof(int)))) dw_Error(MEM_ERR);
if (!(h->high[i]=(int*)malloc(cols*sizeof(int)))) dw_Error(MEM_ERR);
h->Min=CreateMatrix(rows,cols);
h->Max=CreateMatrix(rows,cols);
......@@ -476,8 +476,8 @@ static void Resize(PRECISION x, int *h, PRECISION *min, PRECISION *max, int inte
}
/*
Adds a observation to the histogram. The type of the histogram must
be HISTOGRAM_VARIABLE.
Adds a observation to the histogram. The type of the histogram must
be HISTOGRAM_VARIABLE.
*/
static void AddObservationVariable(PRECISION x, int *h, PRECISION *min, PRECISION *max, int intervals)
{
......@@ -485,7 +485,7 @@ static void AddObservationVariable(PRECISION x, int *h, PRECISION *min, PRECISIO
if ((x < *min) || (x > *max)) Resize(x,h,min,max,intervals);
if (*max > *min)
if (*max > *min)
{
i=(int)(intervals*(x - *min)/(*max - *min));
h[(i < intervals) ? i : intervals-1]++;
......@@ -516,13 +516,13 @@ static void AddObservationFixed(PRECISION x, int *low, int *h, int *high, PRECIS
/*
Returns the level such that the probability of observing an observation
less than or equal to level is percentile. If there is a point mass at
less than or equal to level is percentile. If there is a point mass at
x, and P(y < x) <= percentile <= P(y <= x), then x is returned.
Assumes
Both intervals and sample_size are poitive and low and h[i] are
non-negative. Also if
non-negative. Also if
high = sample_size - (low + h[0] + ... + h[intervals - 1]),
then high is non-negative.
......@@ -560,8 +560,8 @@ static PRECISION Percentile(PRECISION percentile, int low, int *h, PRECISION min
Assumes
Both intervals and sample_size are poitive and low and h[i] are
non-negative. Also, if
non-negative. Also, if
high = sample_size - (low + h[0] + ... + h[intervals - 1]),
then high is non-negative.
......@@ -591,18 +591,18 @@ static PRECISION Cumulative(PRECISION level, int low, int *h, PRECISION min, PRE
if (level >= max) return 1.0;
for (count=low, i=0; i < intervals; count+=h[i++])
if ((min+=inc) >= level)
if ((min+=inc) >= level)
return ((PRECISION)count + (PRECISION)h[i]*(level - min + inc)/inc)/(PRECISION)sample_size;
return 1.0;
}
/*
Returns a histogram over the interval I=[min_out,max_out]. The matrix returned
has bins rows and 2 columns. If inc=(max_out - min_out)/bins, then the first
element of the ith row is
has bins rows and 2 columns. If inc=(max_out - min_out)/bins, then the first
element of the ith row is
min + (i + 0.5)*inc,
min + (i + 0.5)*inc,
which is the mid-point of the ith interval. The second element is
P(min + i*inc < x <= min + (i + 1)*inc)/inc,
......@@ -611,11 +611,11 @@ static PRECISION Cumulative(PRECISION level, int low, int *h, PRECISION min, PRE
Assumes
Both intervals and sample_size are poitive and low and h[i] are
non-negative. Also if
non-negative. Also if
high = sample_size - (low + h[0] + ... + h[intervals - 1]),
then high is non-negative.
then high is non-negative.
If min < max, let inc=(max - min)/intervals and define
......@@ -742,7 +742,7 @@ static TMatrix MakeHistogramAuto(int low, int *h, int high, PRECISION min, PRECI
}
}
}
return MakeHistogram(low,h,min,max,intervals,sample_size,min_out,max_out,bins);
}
......
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