Paulo Grahl | 28 Aug 20:47 2014
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stacked bar chart

Hello Gretl community,

Does anyone have any tip on how to produce stacked bar plots in gretl? 
I've searched around, digged into gnuplot manual, but I'm still having a hard time figuring out how to produce a gretl script to generate stacked bar chart.

Any help?
Thanks
-Paulo


--
Dr. Paulo Gustavo Grahl, CFA
------------------------------------------
pgrahl-Re5JQEeQqe8AvxtiuMwx3w@public.gmane.org
pgrahl-2L7LyNYPm9JfyO9Q7EP/yw@public.gmane.org
skype:paulo.grahl

------------------------------------------
<div><div dir="ltr">Hello Gretl community,<div><br></div>
<div>Does anyone have any tip on how to produce stacked bar plots in gretl?&nbsp;</div>
<div>I've searched around, digged into gnuplot manual, but I'm still having a hard time figuring out how to produce a gretl script to generate stacked bar chart.</div>
<div><br></div>
<div>Any help?</div>
<div>Thanks</div>
<div>-Paulo</div>
<div>
<br clear="all"><div><br></div>-- <br><div dir="ltr">Dr. Paulo Gustavo Grahl, CFA<br>------------------------------------------<br><a href="mailto:pgrahl@..." target="_blank">pgrahl@...</a><br><a href="mailto:pgrahl@..." target="_blank">pgrahl@...</a><br>skype:paulo.grahl<div>
<a href="https://twitter.com/intent/follow?original_referer=https%3A%2F%2Fabout.twitter.com%2Fresources%2Fbuttons&amp;region=follow_link&amp;screen_name=pg1309&amp;tw_p=followbutton&amp;variant=2.0" target="_blank"></a><br>
</div>
<div>
<a href="http://www.linkedin.com/in/pgrahl" target="_blank">www.linkedin.com/in/pgrahl</a><br>
</div>
<div>------------------------------------------<br>
</div>
</div>
</div>
</div></div>
Chi B. Fule | 23 Aug 15:41 2014
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Regressing a Quadratic equation

Hi there,

please may I receive assistance on how to regress a quadratic equation using cross-sectional data?

Thanks in advance

Chi
 
                                                                   

<div><div>
<div><span>Hi there,</span></div>
<div>
<br><span></span>
</div>
<div><span>please may I receive assistance on how to regress a quadratic equation using cross-sectional data?</span></div>
<div>
<br><span></span>
</div>
<div><span>Thanks in advance</span></div>
<div>
<br><span></span>
</div>
<div><span>Chi</span></div>
<div>&nbsp;</div>
<div><span>&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;
 &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;</span></div>
<br>
</div></div>
Henrique Andrade | 11 Aug 21:55 2014
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"sprintf" as a function

Dear Gretl Team,

I'm trying to use the sprintf as a function instead of a command and it is not working here at my Windows Vista
withe the latest Gretl snapshot.

Please take a look at the following script:

<hansl>
open australia.gdt

genr time

ols PAU const time

matrix T = $coeff./$stderr
scalar T_calc = abs(T[2,])
scalar T_tab = critical(t, $T, 0.05)

sprintf Test_1 "t-calculado: %f \n t-tabelado: %f", T_calc, T_tab
print " <at> Test_1"

string Test_2 = sprintf("t-calculado: %f \n t-tabelado: %f", T_calc, T_tab)
print " <at> Test_2"
</hansl>

Best regards,
Henrique

Enviado desde mi iPhone
Artur T. | 11 Aug 18:01 2014

gnuplot shaded areas

Hi all,

I trying to plot a matrix where the last two columns contain information on confidence intervals which I would like to plot as a shaded area.

I wrote a script, but the pdf is not properly compiled giving me an error msg which I don't fully understand. I attached a script which requires the matrix to plot and the path where to store the pdf as inputs.

Unfortunately I can't figure out where the error is.

Thanks for your help in advance.

Best,
Artur
Attachment (example_shaded.inp): application/x-gretlscript, 2524 bytes
<div><div dir="ltr">
<div>
<div>
<div>
<div>Hi all,<br><br>
</div>I trying to plot a matrix where the last two columns contain information on confidence intervals which I would like to plot as a shaded area.<br><br>
</div>I wrote a script, but the pdf is not properly compiled giving me an error msg which I don't fully understand. I attached a script which requires the matrix to plot and the path where to store the pdf as inputs.<br><br>
</div>Unfortunately I can't figure out where the error is. <br><br>
</div>Thanks for your help in advance.<br><br>Best,<br>Artur<br>
</div></div>
Alecos Papadopoulos | 7 Aug 20:26 2014
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Re: Skewness and Excess Kurtosis formulas in Gretl

For what is worth, I was able to determine through numerical experiments, that Gretl uses the "Fisher-Pearson" formulas for calculating the skewness and excess kurtosis coefficients.

This essentially means that for the calculation of these coefficients, all sample means involved (even the sample variance/standard deviation) are calculated using the factor (1/n), and that no bias-correction terms appear.
I am writing this informatively - I have no settled opinion on which alternative formula should be preferred.

So

Skewness Coefficient (this version is usually denoted "g1")
Numerator: (1/n)(Σ(x_i - mean(X))^3)
Denominator : [(1/n) Σ(x_i - mean(X))^2]^(3/2)

(Excess) Kurtosis Coefficient (this version is usually denoted "g2")
Numerator : (1/n)(Σ(x_i - mean(X))^4)
Denominator : [(1/n) Σ[x_i - mean(X)]^2]^2

and we further subtract "3" after we calculate the ratio to obtain the "excess" over the kurtosis of the normal distribution.

References for the names and presentations of various alternatives

Joanes, D. N., & Gill, C. A. (1998). Comparing measures of sample skewness and kurtosis. Journal of the Royal Statistical Society: Series D (The Statistician), 47(1), 183-189.
Doane, D. P., & Seward, L. E. (2011). Measuring skewness: a forgotten statistic. Journal of Statistics Education, 19(2), 1-18.
Alecos Papadopoulos Athens University of Economics and Business, Greece Department of Economics cell:+30-6945-378680 fax: +30-210-8259763 skype:alecos.papadopoulos On 7/8/2014 19:00, gretl-users-request-npDYnXcwJHngpn9g0Uvcdg@public.gmane.org wrote:
Yes. I might just add that our measures are in agreement with those of the "moments" package for R, except that R gives total rather than excess kurtosis. Allin Cottrell

<div>
    <div class="moz-cite-prefix">For what is worth, I was able to
      determine through numerical experiments, that Gretl uses the
      "Fisher-Pearson" formulas for calculating the skewness and excess
      kurtosis coefficients.<br><br>
      This essentially means that for the calculation of these
      coefficients, all sample means involved (even the sample
      variance/standard deviation) are calculated using the factor
      (1/n), and that no bias-correction terms appear.<br>
      I am writing this informatively - I have no settled opinion on
      which alternative formula should be preferred.<br><br>
      So<br><br>Skewness Coefficient (this version is usually denoted "g1")<br>
      Numerator: (1/n)(&Sigma;(x_i
      - mean(X))^3)<br>
      Denominator : [(1/n) &Sigma;(x_i -
      mean(X))^2]^(3/2)<br><br>(Excess) Kurtosis Coefficient (this
              version is usually denoted "g2")<br>
              Numerator : (1/n)(&Sigma;(x_i
      - mean(X))^4)<br>Denominator : [(1/n) &Sigma;[x_i
      - mean(X)]^2]^2<br><br>
              and we further subtract "3" after we calculate the ratio
              to obtain the "excess" over the kurtosis of the normal
              distribution.<br><br>
              References for the names and presentations of various
              alternatives<br><br>Joanes, D. N., &amp; Gill, C. A.
      (1998). Comparing measures of sample skewness and kurtosis. Journal
        of the Royal Statistical Society: Series D (The Statistician),
      47(1), 183-189.<br>
      Doane, D. P., &amp; Seward, L. E. (2011). Measuring skewness: a
      forgotten statistic. Journal of Statistics Education, 19(2),
      1-18.<br>Alecos Papadopoulos
Athens University of Economics and Business, Greece
Department of Economics
cell:+30-6945-378680
fax: +30-210-8259763
<a class="moz-txt-link-freetext" href="skype:alecos.papadopoulos">skype:alecos.papadopoulos</a>
      On 7/8/2014 19:00, <a class="moz-txt-link-abbreviated" href="mailto:gretl-users-request@...">gretl-users-request@...</a> wrote:<br>
</div>
    <blockquote cite="mid:mailman.13.1407427202.19658.gretl-users@..." type="cite">
      Yes. I might just add that our measures are in agreement with those of the 
"moments" package for R, except that R gives total rather than excess 
kurtosis.

Allin Cottrell
    </blockquote>
    <br>
</div>
Danilo Aulicino | 7 Aug 10:35 2014
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Unscribe from mailing list

Don't you send me new mail,please
Thakx

Danilo Aulicino
Tel. 3291288752
Marco Lilla | 6 Aug 19:57 2014
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Re: Gretl-users Digest, Vol 91, Issue 2


gretl-users-request@... ha scritto:

Send Gretl-users mailing list submissions to
	gretl-users@...

To subscribe or unsubscribe via the World Wide Web, visit
	http://lists.wfu.edu/mailman/listinfo/gretl-users
or, via email, send a message with subject or body 'help' to
	gretl-users-request@...

You can reach the person managing the list at
	gretl-users-owner@...

When replying, please edit your Subject line so it is more specific
than "Re: Contents of Gretl-users digest..."

Today's Topics:

   1. Re: Generate Discrete Uniform with negative bounds
      (Alecos Papadopoulos)
   2. Re: Generate Discrete Uniform with negative bounds (Annaert Jan)
   3. Re: Generate Discrete Uniform with negative bounds
      (Allin Cottrell)

----------------------------------------------------------------------

Message: 1
Date: Wed, 06 Aug 2014 06:31:41 +0300
From: Alecos Papadopoulos <papadopalex@...>
Subject: Re: [Gretl-users] Generate Discrete Uniform with negative
	bounds
To: gretl-users@...
Message-ID: <53E1A19D.3030402@...>
Content-Type: text/plain; charset=ISO-8859-7; format=flowed

Good afternoon. I tried to generate discrete uniform random variables 
using randgen, but it appears that the function cannot take negative 
values as bounds for the distribution (if both minimum and maximum are 
positive, then everything works fine. If either one or both bounds are 
negative numbers, it goes berserk).
The script is

nulldata 100
genr scalar lb=-5
genr scalar ub=1
genr series Z1 = randgen(i,lb,ub)

and the summary statistics are

Summary statistics, using the observations 1 - 100
for the variable 'Z1' (100 valid observations)

   Mean                    2.7488e+009
   Median                  4.2950e+009
   Minimum                     0.00000
   Maximum                 4.2950e+009
   Standard deviation     allo  2.0720e+009
   C.V.                        0.75378
   Skewness                   -0.58333
   Ex. kurtosis                -1.6597
   5% percentile               0.00000
   95% percentile          4.2950e+009
   Interquartile range     4.2950e+009
   Missing obs.                      0

-- 

gretl-users-request@... ha scritto:

Send Gretl-users mailing list submissions to
	gretl-users@...

To subscribe or unsubscribe via the World Wide Web, visit
	http://lists.wfu.edu/mailman/listinfo/gretl-users
or, via email, send a message with subject or body 'help' to
	gretl-users-request@...

You can reach the person managing the list at
	gretl-users-owner@...

When replying, please edit your Subject line so it is more specific
than "Re: Contents of Gretl-users digest..."

Today's Topics:

   1. Re: Generate Discrete Uniform with negative bounds
      (Alecos Papadopoulos)
   2. Re: Generate Discrete Uniform with negative bounds (Annaert Jan)
   3. Re: Generate Discrete Uniform with negative bounds
      (Allin Cottrell)

----------------------------------------------------------------------

Message: 1
Date: Wed, 06 Aug 2014 06:31:41 +0300
From: Alecos Papadopoulos <papadopalex@...>
Subject: Re: [Gretl-users] Generate Discrete Uniform with negative
	bounds
To: gretl-users@...
Message-ID: <53E1A19D.3030402@...>
Content-Type: text/plain; charset=ISO-8859-7; format=flowed

Good afternoon. I tried to generate discrete uniform random variables 
using randgen, but it appears that the function cannot take negative 
values as bounds for the distribution (if both minimum and maximum are 
positive, then everything works fine. If either one or both bounds are 
negative numbers, it goes berserk).
The script is

nulldata 100
genr scalar lb=-5
genr scalar ub=1
genr series Z1 = randgen(i,lb,ub)

and the summary statistics are

Summary statistics, using the observations 1 - 100
for the variable 'Z1' (100 valid observations)

   Mean                    2.7488e+009
   Median                  4.2950e+009
   Minimum                     0.00000
   Maximum                 4.2950e+009
   Standard deviation      2.0720e+009
   C.V.                        0.75378
   Skewness                   -0.58333
   Ex. kurtosis                -1.6597
   5% percentile               0.00000
   95% percentile          4.2950e+009
   Interquartile range     4.2950e+009
   Missing obs.                      0

--

-- 

Alecos Papadopoulos | 6 Aug 05:31 2014
Picon

Re: Generate Discrete Uniform with negative bounds

Good afternoon. I tried to generate discrete uniform random variables 
using randgen, but it appears that the function cannot take negative 
values as bounds for the distribution (if both minimum and maximum are 
positive, then everything works fine. If either one or both bounds are 
negative numbers, it goes berserk).
The script is

nulldata 100
genr scalar lb=-5
genr scalar ub=1
genr series Z1 = randgen(i,lb,ub)

and the summary statistics are

Summary statistics, using the observations 1 - 100
for the variable 'Z1' (100 valid observations)

   Mean                    2.7488e+009
   Median                  4.2950e+009
   Minimum                     0.00000
   Maximum                 4.2950e+009
   Standard deviation      2.0720e+009
   C.V.                        0.75378
   Skewness                   -0.58333
   Ex. kurtosis                -1.6597
   5% percentile               0.00000
   95% percentile          4.2950e+009
   Interquartile range     4.2950e+009
   Missing obs.                      0

--

-- 
Alecos Papadopoulos
Athens University of Economics and Business, Greece
Department of Economics
cell:+30-6945-378680
fax: +30-210-8259763
skype:alecos.papadopoulos

Alecos Papadopoulos | 5 Aug 17:34 2014
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Re: Expression for sample excess kurtosis and sample skewness calculation in Gretl

Good afternoon.
Is it possible to provide the exact expressions for the calculation of 
sample excess kurtosis, and for sample skewness, that Gretl uses? I 
wasn't able to find them in the User Guide or in the Help menu, and 
there are varying expressions available in the literature, with 
different bias-correction terms.
Thank you.

PS : The swinging MLE appears to work fine.

--

-- 
Alecos Papadopoulos
Athens University of Economics and Business, Greece
Department of Economics
cell:+30-6945-378680
fax: +30-210-8259763
skype:alecos.papadopoulos

Sven Schreiber | 23 Jul 14:17 2014
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Picon

Variable generation full vs. restricted sample

Hi,

obviously it's absolutely essential to be able to create variables only 
for the currently active subsample. But I'm wondering, is there another 
(easier) way to generate variables also for the full workfile sample 
range without temporarily removing and then later re-applying the sample 
restrictions?

Perhaps something like "series mynew = log(income) --full" if you 
understand what I mean by that.

thanks for suggestions,
sven
Logan Kelly | 19 Jul 21:28 2014

Question about SVAR

Hello,

 

I am estimating a “plain” model with the SVAR package  because the native irf() function returns :

 

Matrix is not positive definite

 

(Note: the reason for this error is discussed in another post)

 

Thus, I am trying the SVAR package, but the “actual” irf estimate is always above the bootstraped confidence bands. I am using the bias corrected bootstrapping method (Killian 1989).

 

I am thinking this must be a problem with my data, not SVAR or gretl? Does that sound right?

 

SVAR: 0.997

gretl:  1.9.90

os: win 7 64 bit

 

Thanks,

 

Logan

<div>
<div class="WordSection1">
<p class="MsoNormal">Hello,<p></p></p>
<p class="MsoNormal"><p>&nbsp;</p></p>
<p class="MsoNormal">I am estimating a &ldquo;plain&rdquo; model with the SVAR package&nbsp; because the native irf() function returns :<p></p></p>
<p class="MsoNormal"><p>&nbsp;</p></p>
<p class="MsoNormal">Matrix is not positive definite<p></p></p>
<p class="MsoNormal"><p>&nbsp;</p></p>
<p class="MsoNormal">(Note: the reason for this error is discussed in another post)<p></p></p>
<p class="MsoNormal"><p>&nbsp;</p></p>
<p class="MsoNormal">Thus, I am trying the SVAR package, but the &ldquo;actual&rdquo; irf estimate is always above the bootstraped confidence bands. I am using the bias corrected bootstrapping method (Killian 1989).<p></p></p>
<p class="MsoNormal"><p>&nbsp;</p></p>
<p class="MsoNormal">I am thinking this must be a problem with my data, not SVAR or gretl? Does that sound right?<p></p></p>
<p class="MsoNormal"><p>&nbsp;</p></p>
<p class="MsoNormal">SVAR: 0.997<p></p></p>
<p class="MsoNormal">gretl: &nbsp;1.9.90<p></p></p>
<p class="MsoNormal">os: win 7 64 bit<p></p></p>
<p class="MsoNormal"><p>&nbsp;</p></p>
<p class="MsoNormal">Thanks,<p></p></p>
<p class="MsoNormal"><p>&nbsp;</p></p>
<p class="MsoNormal">Logan<p></p></p>
</div>
</div>

Gmane