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    <title>topic Why the WARNING occurs? in SAS Programming</title>
    <link>https://communities.sas.com/t5/SAS-Programming/Why-the-WARNING-occurs/m-p/333606#M272149</link>
    <description>&lt;P&gt;&lt;STRONG&gt;Hi,&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;When I run the nlmixed model, I&amp;nbsp;keep getting warning like this&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: By default, formatted unique SUBJECT= variable values are used. In releases prior to&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; SAS/STAT 13.1, by default, SUBJECT= variable values were not examined for uniqueness. To&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; revert to the previous behavior, specify the NOSORTSUB option in the PROC NLMIXED statement.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: Convergence criterion (GCONV=1E-8) satisfied.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: At least one element of the gradient is greater than 1e-3.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: Execution error while processing ESTIMATE statement.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: The SAS System stopped processing this step because of errors.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;WARNING: The data set WORK.DATA1 may be incomplete.&amp;nbsp; When this step was stopped there were 382068&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; observations and 33 variables.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;WARNING: Data set WORK.DATA1 was not replaced because this step was stopped.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;WARNING: The data set WORK.DATA2 may be incomplete.&amp;nbsp; When this step was stopped there were 382068&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; observations and 33 variables.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;WARNING: Data set WORK.DATA2 was not replaced because this step was stopped.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Here is the code:&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;%macro focalvar (focalvar);&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;proc nlmixed data=base qpoints=5;&lt;/P&gt;&lt;P class="p1"&gt;/* define initial values and bounds */&lt;/P&gt;&lt;P class="p1"&gt;parms alpha0=-1 alpha1=1 alpha2=1 alpha3=1 alpha4=1 alpha5=1 alpha6=1 alpha7=1 beta0=1 beta1=1 beta2=1 beta3=1 beta4=1 beta5=1 beta6=1 beta7=1 delta0=1 delta1=2 delta2=2 delta3=2 delta4=2 delta5=2&lt;SPAN class="Apple-converted-space"&gt;&amp;nbsp; &lt;/SPAN&gt;delta6=2 delta7=2 var1=1 var2=1 cov12=.5 k=2;&lt;/P&gt;&lt;P class="p1"&gt;bounds var1 var2 &amp;gt;=0;&lt;/P&gt;&lt;P class="p1"&gt;/* Part I log-likelihood */&lt;/P&gt;&lt;P class="p1"&gt;teta=alpha0 + a + alpha1*during + alpha2*exposed2 + alpha3*during*exposed2+alpha4*&amp;amp;focalvar+alpha5*&amp;amp;focalvar*during+alpha6*&amp;amp;focalvar*exposed2+alpha7*&amp;amp;focalvar*during*exposed2;&lt;/P&gt;&lt;P class="p1"&gt;expteta=exp(teta);&lt;/P&gt;&lt;P class="p1"&gt;p=expteta/(1+expteta);&lt;/P&gt;&lt;P class="p1"&gt;if new_rate=0 then loglik=log(1-p);&lt;/P&gt;&lt;P class="p1"&gt;/* Part II log-likelihood */&lt;/P&gt;&lt;P class="p1"&gt;if new_rate=1 then do;&lt;/P&gt;&lt;P class="p1"&gt;mu=beta0 + b + beta1*during + beta2*exposed2 + beta3*during*exposed2+beta4*&amp;amp;focalvar+beta5*&amp;amp;focalvar*during+beta6*&amp;amp;focalvar*exposed2+beta7*&amp;amp;focalvar*during*exposed2; /* Mean of gen. gamma dist. */&lt;/P&gt;&lt;P class="p1"&gt;sigma=exp((delta0 + delta1*during + delta2*exposed2 + delta3*during*exposed2+delta4*&amp;amp;focalvar+delta5*&amp;amp;focalvar*during+delta6*&amp;amp;focalvar*exposed2+delta7*&amp;amp;focalvar*during*exposed2)/2); /* Scale of gen. gamma dist. */&lt;/P&gt;&lt;P class="p1"&gt;eta=abs(k) ** (-2);&lt;/P&gt;&lt;P class="p1"&gt;u=sign(k)*(log(rate)-mu)/sigma;&lt;/P&gt;&lt;P class="p1"&gt;value1=eta *log (eta) - log(sigma) -.5 * log(eta) - lgamma(eta);&lt;/P&gt;&lt;P class="p1"&gt;loglik=log(p) + value1 + u *sqrt(eta) - eta * exp(abs(k)* u);&lt;/P&gt;&lt;P class="p1"&gt;end;&lt;/P&gt;&lt;P class="p1"&gt;/* fit the model above */&lt;/P&gt;&lt;P class="p1"&gt;model rate ~ general(loglik);&lt;/P&gt;&lt;P class="p1"&gt;random a b ~ normal([0, 0], [var1, cov12, var2]) subject=household_key;&lt;/P&gt;&lt;P class="p1"&gt;/* generate empirical Bayes estimates for random effects&lt;/P&gt;&lt;P class="p1"&gt;and store them in SAS datasets data1 and data2; */&lt;/P&gt;&lt;P class="p1"&gt;predict a out=data1;&lt;/P&gt;&lt;P class="p1"&gt;predict b out=data2;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '1' alpha1+log(1+exp(alpha0))-log(1+exp(alpha0+alpha1)) +beta1 + log(k**2)/k*( exp((delta0+delta1)/2)-exp(delta0/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1)/2)/k) / gamma(1/k**2+exp(delta0/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '2' alpha2+log(1+exp(alpha0))-log(1+exp(alpha0+alpha2)) +beta2 + log(k**2)/k*( exp((delta0+delta2)/2)-exp(delta0/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta2)/2)/k) / gamma(1/k**2+exp(delta0/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '3' alpha3+log(1+exp(alpha0+alpha1+alpha2))-log(1+exp(alpha0+alpha1+alpha2+alpha3)) +beta3 + log(k**2)/k*( exp((delta0+delta1+delta2+delta3)/2)-exp((delta0+delta1+delta2)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1+delta2+delta3)/2)/k) / gamma(1/k**2+exp((delta0+delta1+delta2)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '4' alpha4+log(1+exp(alpha0))-log(1+exp(alpha0+alpha4)) +beta4 + log(k**2)/k*( exp((delta0+delta4)/2)-exp(delta0/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta4)/2)/k) / gamma(1/k**2+exp(delta0/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '5' alpha5+log(1+exp(alpha0+alpha1+alpha4))-log(1+exp(alpha0+alpha1+alpha4+alpha5)) +beta5 + log(k**2)/k*( exp((delta0+delta1+delta4+delta5)/2)-exp((delta0+delta1+delta4)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1+delta4+delta5)/2)/k) / gamma(1/k**2+exp((delta0+delta1+delta4)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '6' alpha6+log(1+exp(alpha0+alpha2+alpha4))-log(1+exp(alpha0+alpha2+alpha4+alpha6)) +beta6 + log(k**2)/k*( exp((delta0+delta2+delta4+delta6)/2)-exp((delta0+delta2+delta4)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta2+delta4+delta6)/2)/k) / gamma(1/k**2+exp((delta0+delta2+delta4)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '7' alpha7+log(1+exp(alpha0+alpha1+alpha2+alpha3+alpha4+alpha5+alpha6))-log(1+exp(alpha0+alpha1+alpha2+alpha3+alpha4+alpha5+alpha6+alpha7)) +beta7 + log(k**2)/k*( exp((delta0+delta1+delta2+delta3+delta4+delta5+delta6+delta7)/2)-exp((delta0+delta1+delta2+delta3+delta4+delta5+delta6)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1+delta2+delta4+delta7)/2)/k) / gamma(1/k**2+exp((delta0+delta1+delta2+delta3+delta4+delta5+delta6)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;%mend focalvar;&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate1);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate2);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate3);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate4);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate5);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate6);&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate7);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate8);&lt;/P&gt;&lt;P class="p1"&gt;run;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Except for first two macros, others run successfully. It is so weird....&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&lt;STRONG&gt;&lt;SPAN class="s1"&gt;Thanks!!!!!&lt;/SPAN&gt;&lt;/STRONG&gt;&lt;/P&gt;</description>
    <pubDate>Sat, 18 Feb 2017 13:59:48 GMT</pubDate>
    <dc:creator>xg405012</dc:creator>
    <dc:date>2017-02-18T13:59:48Z</dc:date>
    <item>
      <title>Why the WARNING occurs?</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Why-the-WARNING-occurs/m-p/333606#M272149</link>
      <description>&lt;P&gt;&lt;STRONG&gt;Hi,&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;When I run the nlmixed model, I&amp;nbsp;keep getting warning like this&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: By default, formatted unique SUBJECT= variable values are used. In releases prior to&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; SAS/STAT 13.1, by default, SUBJECT= variable values were not examined for uniqueness. To&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; revert to the previous behavior, specify the NOSORTSUB option in the PROC NLMIXED statement.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: Convergence criterion (GCONV=1E-8) satisfied.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: At least one element of the gradient is greater than 1e-3.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: Execution error while processing ESTIMATE statement.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;NOTE: The SAS System stopped processing this step because of errors.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;WARNING: The data set WORK.DATA1 may be incomplete.&amp;nbsp; When this step was stopped there were 382068&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; observations and 33 variables.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;WARNING: Data set WORK.DATA1 was not replaced because this step was stopped.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;WARNING: The data set WORK.DATA2 may be incomplete.&amp;nbsp; When this step was stopped there were 382068&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp;&amp;nbsp; observations and 33 variables.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&lt;SPAN class="s1"&gt;WARNING: Data set WORK.DATA2 was not replaced because this step was stopped.&lt;/SPAN&gt;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Here is the code:&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;%macro focalvar (focalvar);&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;proc nlmixed data=base qpoints=5;&lt;/P&gt;&lt;P class="p1"&gt;/* define initial values and bounds */&lt;/P&gt;&lt;P class="p1"&gt;parms alpha0=-1 alpha1=1 alpha2=1 alpha3=1 alpha4=1 alpha5=1 alpha6=1 alpha7=1 beta0=1 beta1=1 beta2=1 beta3=1 beta4=1 beta5=1 beta6=1 beta7=1 delta0=1 delta1=2 delta2=2 delta3=2 delta4=2 delta5=2&lt;SPAN class="Apple-converted-space"&gt;&amp;nbsp; &lt;/SPAN&gt;delta6=2 delta7=2 var1=1 var2=1 cov12=.5 k=2;&lt;/P&gt;&lt;P class="p1"&gt;bounds var1 var2 &amp;gt;=0;&lt;/P&gt;&lt;P class="p1"&gt;/* Part I log-likelihood */&lt;/P&gt;&lt;P class="p1"&gt;teta=alpha0 + a + alpha1*during + alpha2*exposed2 + alpha3*during*exposed2+alpha4*&amp;amp;focalvar+alpha5*&amp;amp;focalvar*during+alpha6*&amp;amp;focalvar*exposed2+alpha7*&amp;amp;focalvar*during*exposed2;&lt;/P&gt;&lt;P class="p1"&gt;expteta=exp(teta);&lt;/P&gt;&lt;P class="p1"&gt;p=expteta/(1+expteta);&lt;/P&gt;&lt;P class="p1"&gt;if new_rate=0 then loglik=log(1-p);&lt;/P&gt;&lt;P class="p1"&gt;/* Part II log-likelihood */&lt;/P&gt;&lt;P class="p1"&gt;if new_rate=1 then do;&lt;/P&gt;&lt;P class="p1"&gt;mu=beta0 + b + beta1*during + beta2*exposed2 + beta3*during*exposed2+beta4*&amp;amp;focalvar+beta5*&amp;amp;focalvar*during+beta6*&amp;amp;focalvar*exposed2+beta7*&amp;amp;focalvar*during*exposed2; /* Mean of gen. gamma dist. */&lt;/P&gt;&lt;P class="p1"&gt;sigma=exp((delta0 + delta1*during + delta2*exposed2 + delta3*during*exposed2+delta4*&amp;amp;focalvar+delta5*&amp;amp;focalvar*during+delta6*&amp;amp;focalvar*exposed2+delta7*&amp;amp;focalvar*during*exposed2)/2); /* Scale of gen. gamma dist. */&lt;/P&gt;&lt;P class="p1"&gt;eta=abs(k) ** (-2);&lt;/P&gt;&lt;P class="p1"&gt;u=sign(k)*(log(rate)-mu)/sigma;&lt;/P&gt;&lt;P class="p1"&gt;value1=eta *log (eta) - log(sigma) -.5 * log(eta) - lgamma(eta);&lt;/P&gt;&lt;P class="p1"&gt;loglik=log(p) + value1 + u *sqrt(eta) - eta * exp(abs(k)* u);&lt;/P&gt;&lt;P class="p1"&gt;end;&lt;/P&gt;&lt;P class="p1"&gt;/* fit the model above */&lt;/P&gt;&lt;P class="p1"&gt;model rate ~ general(loglik);&lt;/P&gt;&lt;P class="p1"&gt;random a b ~ normal([0, 0], [var1, cov12, var2]) subject=household_key;&lt;/P&gt;&lt;P class="p1"&gt;/* generate empirical Bayes estimates for random effects&lt;/P&gt;&lt;P class="p1"&gt;and store them in SAS datasets data1 and data2; */&lt;/P&gt;&lt;P class="p1"&gt;predict a out=data1;&lt;/P&gt;&lt;P class="p1"&gt;predict b out=data2;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '1' alpha1+log(1+exp(alpha0))-log(1+exp(alpha0+alpha1)) +beta1 + log(k**2)/k*( exp((delta0+delta1)/2)-exp(delta0/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1)/2)/k) / gamma(1/k**2+exp(delta0/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '2' alpha2+log(1+exp(alpha0))-log(1+exp(alpha0+alpha2)) +beta2 + log(k**2)/k*( exp((delta0+delta2)/2)-exp(delta0/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta2)/2)/k) / gamma(1/k**2+exp(delta0/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '3' alpha3+log(1+exp(alpha0+alpha1+alpha2))-log(1+exp(alpha0+alpha1+alpha2+alpha3)) +beta3 + log(k**2)/k*( exp((delta0+delta1+delta2+delta3)/2)-exp((delta0+delta1+delta2)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1+delta2+delta3)/2)/k) / gamma(1/k**2+exp((delta0+delta1+delta2)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '4' alpha4+log(1+exp(alpha0))-log(1+exp(alpha0+alpha4)) +beta4 + log(k**2)/k*( exp((delta0+delta4)/2)-exp(delta0/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta4)/2)/k) / gamma(1/k**2+exp(delta0/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '5' alpha5+log(1+exp(alpha0+alpha1+alpha4))-log(1+exp(alpha0+alpha1+alpha4+alpha5)) +beta5 + log(k**2)/k*( exp((delta0+delta1+delta4+delta5)/2)-exp((delta0+delta1+delta4)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1+delta4+delta5)/2)/k) / gamma(1/k**2+exp((delta0+delta1+delta4)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '6' alpha6+log(1+exp(alpha0+alpha2+alpha4))-log(1+exp(alpha0+alpha2+alpha4+alpha6)) +beta6 + log(k**2)/k*( exp((delta0+delta2+delta4+delta6)/2)-exp((delta0+delta2+delta4)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta2+delta4+delta6)/2)/k) / gamma(1/k**2+exp((delta0+delta2+delta4)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '7' alpha7+log(1+exp(alpha0+alpha1+alpha2+alpha3+alpha4+alpha5+alpha6))-log(1+exp(alpha0+alpha1+alpha2+alpha3+alpha4+alpha5+alpha6+alpha7)) +beta7 + log(k**2)/k*( exp((delta0+delta1+delta2+delta3+delta4+delta5+delta6+delta7)/2)-exp((delta0+delta1+delta2+delta3+delta4+delta5+delta6)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1+delta2+delta4+delta7)/2)/k) / gamma(1/k**2+exp((delta0+delta1+delta2+delta3+delta4+delta5+delta6)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;%mend focalvar;&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate1);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate2);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate3);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate4);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate5);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate6);&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate7);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate8);&lt;/P&gt;&lt;P class="p1"&gt;run;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&lt;STRONG&gt;Except for first two macros, others run successfully. It is so weird....&lt;/STRONG&gt;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&lt;STRONG&gt;&lt;SPAN class="s1"&gt;Thanks!!!!!&lt;/SPAN&gt;&lt;/STRONG&gt;&lt;/P&gt;</description>
      <pubDate>Sat, 18 Feb 2017 13:59:48 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Why-the-WARNING-occurs/m-p/333606#M272149</guid>
      <dc:creator>xg405012</dc:creator>
      <dc:date>2017-02-18T13:59:48Z</dc:date>
    </item>
    <item>
      <title>Re: Why the WARNING occurs?</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Why-the-WARNING-occurs/m-p/333610#M272150</link>
      <description>&lt;P&gt;Let's see the program from which this originated.&amp;nbsp; Do you have OPTIONS MPRINT enabled so that you can show us the offending sas code reprinted on the log?&lt;/P&gt;</description>
      <pubDate>Thu, 16 Feb 2017 22:54:43 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Why-the-WARNING-occurs/m-p/333610#M272150</guid>
      <dc:creator>mkeintz</dc:creator>
      <dc:date>2017-02-16T22:54:43Z</dc:date>
    </item>
    <item>
      <title>Re: Why the WARNING occurs?</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Why-the-WARNING-occurs/m-p/334061#M272151</link>
      <description>&lt;P&gt;Thanks! Here is the code. It may seems a little bit completed:&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;%macro focalvar (focalvar);&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;proc nlmixed data=base qpoints=5;&lt;/P&gt;&lt;P class="p1"&gt;/* define initial values and bounds */&lt;/P&gt;&lt;P class="p1"&gt;parms alpha0=-1 alpha1=1 alpha2=1 alpha3=1 alpha4=1 alpha5=1 alpha6=1 alpha7=1 beta0=1 beta1=1 beta2=1 beta3=1 beta4=1 beta5=1 beta6=1 beta7=1 delta0=1 delta1=2 delta2=2 delta3=2 delta4=2 delta5=2&lt;SPAN class="Apple-converted-space"&gt;&amp;nbsp; &lt;/SPAN&gt;delta6=2 delta7=2 var1=1 var2=1 cov12=.5 k=2;&lt;/P&gt;&lt;P class="p1"&gt;bounds var1 var2 &amp;gt;=0;&lt;/P&gt;&lt;P class="p1"&gt;/* Part I log-likelihood */&lt;/P&gt;&lt;P class="p1"&gt;teta=alpha0 + a + alpha1*during + alpha2*exposed2 + alpha3*during*exposed2+alpha4*&amp;amp;focalvar+alpha5*&amp;amp;focalvar*during+alpha6*&amp;amp;focalvar*exposed2+alpha7*&amp;amp;focalvar*during*exposed2;&lt;/P&gt;&lt;P class="p1"&gt;expteta=exp(teta);&lt;/P&gt;&lt;P class="p1"&gt;p=expteta/(1+expteta);&lt;/P&gt;&lt;P class="p1"&gt;if new_rate=0 then loglik=log(1-p);&lt;/P&gt;&lt;P class="p1"&gt;/* Part II log-likelihood */&lt;/P&gt;&lt;P class="p1"&gt;if new_rate=1 then do;&lt;/P&gt;&lt;P class="p1"&gt;mu=beta0 + b + beta1*during + beta2*exposed2 + beta3*during*exposed2+beta4*&amp;amp;focalvar+beta5*&amp;amp;focalvar*during+beta6*&amp;amp;focalvar*exposed2+beta7*&amp;amp;focalvar*during*exposed2; /* Mean of gen. gamma dist. */&lt;/P&gt;&lt;P class="p1"&gt;sigma=exp((delta0 + delta1*during + delta2*exposed2 + delta3*during*exposed2+delta4*&amp;amp;focalvar+delta5*&amp;amp;focalvar*during+delta6*&amp;amp;focalvar*exposed2+delta7*&amp;amp;focalvar*during*exposed2)/2); /* Scale of gen. gamma dist. */&lt;/P&gt;&lt;P class="p1"&gt;eta=abs(k) ** (-2);&lt;/P&gt;&lt;P class="p1"&gt;u=sign(k)*(log(rate)-mu)/sigma;&lt;/P&gt;&lt;P class="p1"&gt;value1=eta *log (eta) - log(sigma) -.5 * log(eta) - lgamma(eta);&lt;/P&gt;&lt;P class="p1"&gt;loglik=log(p) + value1 + u *sqrt(eta) - eta * exp(abs(k)* u);&lt;/P&gt;&lt;P class="p1"&gt;end;&lt;/P&gt;&lt;P class="p1"&gt;/* fit the model above */&lt;/P&gt;&lt;P class="p1"&gt;model rate ~ general(loglik);&lt;/P&gt;&lt;P class="p1"&gt;random a b ~ normal([0, 0], [var1, cov12, var2]) subject=household_key;&lt;/P&gt;&lt;P class="p1"&gt;/* generate empirical Bayes estimates for random effects&lt;/P&gt;&lt;P class="p1"&gt;and store them in SAS datasets data1 and data2; */&lt;/P&gt;&lt;P class="p1"&gt;predict a out=data1;&lt;/P&gt;&lt;P class="p1"&gt;predict b out=data2;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '1' alpha1+log(1+exp(alpha0))-log(1+exp(alpha0+alpha1)) +beta1 + log(k**2)/k*( exp((delta0+delta1)/2)-exp(delta0/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1)/2)/k) / gamma(1/k**2+exp(delta0/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '2' alpha2+log(1+exp(alpha0))-log(1+exp(alpha0+alpha2)) +beta2 + log(k**2)/k*( exp((delta0+delta2)/2)-exp(delta0/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta2)/2)/k) / gamma(1/k**2+exp(delta0/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '3' alpha3+log(1+exp(alpha0+alpha1+alpha2))-log(1+exp(alpha0+alpha1+alpha2+alpha3)) +beta3 + log(k**2)/k*( exp((delta0+delta1+delta2+delta3)/2)-exp((delta0+delta1+delta2)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1+delta2+delta3)/2)/k) / gamma(1/k**2+exp((delta0+delta1+delta2)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '4' alpha4+log(1+exp(alpha0))-log(1+exp(alpha0+alpha4)) +beta4 + log(k**2)/k*( exp((delta0+delta4)/2)-exp(delta0/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta4)/2)/k) / gamma(1/k**2+exp(delta0/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '5' alpha5+log(1+exp(alpha0+alpha1+alpha4))-log(1+exp(alpha0+alpha1+alpha4+alpha5)) +beta5 + log(k**2)/k*( exp((delta0+delta1+delta4+delta5)/2)-exp((delta0+delta1+delta4)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1+delta4+delta5)/2)/k) / gamma(1/k**2+exp((delta0+delta1+delta4)/2)/k) );&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '6' alpha6+log(1+exp(alpha0+alpha2+alpha4))-log(1+exp(alpha0+alpha2+alpha4+alpha6)) +beta6 + log(k**2)/k*( exp((delta0+delta2+delta4+delta6)/2)-exp((delta0+delta2+delta4)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta2+delta4+delta6)/2)/k) / gamma(1/k**2+exp((delta0+delta2+delta4)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;estimate '7' alpha7+log(1+exp(alpha0+alpha1+alpha2+alpha3+alpha4+alpha5+alpha6))-log(1+exp(alpha0+alpha1+alpha2+alpha3+alpha4+alpha5+alpha6+alpha7)) +beta7 + log(k**2)/k*( exp((delta0+delta1+delta2+delta3+delta4+delta5+delta6+delta7)/2)-exp((delta0+delta1+delta2+delta3+delta4+delta5+delta6)/2) ) +&lt;/P&gt;&lt;P class="p1"&gt;log( gamma(1/k**2+exp((delta0+delta1+delta2+delta4+delta7)/2)/k) / gamma(1/k**2+exp((delta0+delta1+delta2+delta3+delta4+delta5+delta6)/2)/k) );&amp;nbsp;&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;%mend focalvar;&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate1);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate2);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate3);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate4);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate5);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate6);&lt;/P&gt;&lt;P class="p2"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate7);&lt;/P&gt;&lt;P class="p1"&gt;%focalvar (cate8);&lt;/P&gt;&lt;P class="p1"&gt;run;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;The thing is, except for the first two macros, we got results of others.&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;&amp;nbsp;&lt;/P&gt;&lt;P class="p1"&gt;Thanks!&lt;/P&gt;</description>
      <pubDate>Sat, 18 Feb 2017 13:56:21 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Why-the-WARNING-occurs/m-p/334061#M272151</guid>
      <dc:creator>xg405012</dc:creator>
      <dc:date>2017-02-18T13:56:21Z</dc:date>
    </item>
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