diff --git a/.gitignore b/.gitignore
index cf5438fe697..8402d16e054 100644
--- a/.gitignore
+++ b/.gitignore
@@ -27,6 +27,7 @@ configure.log
 *.oct
 .localvimrc
 *.DS_Store
+cscope.*
 
 *~
 \#*\#
diff --git a/src/shogun/base/init.cpp b/src/shogun/base/init.cpp
index 33c3ac86416..e3281ca9927 100644
--- a/src/shogun/base/init.cpp
+++ b/src/shogun/base/init.cpp
@@ -15,6 +15,8 @@
 #include <shogun/lib/Map.h>
 #include <shogun/base/Parallel.h>
 #include <shogun/base/Version.h>
+#include <stdlib.h>
+#include <string.h>
 
 #ifdef TRACE_MEMORY_ALLOCS
 shogun::CMap<void*, shogun::MemoryBlock>* sg_mallocs=NULL;
@@ -72,6 +74,8 @@ namespace shogun
 		sg_print_warning=print_warning;
 		sg_print_error=print_error;
 		sg_cancel_computations=cancel_computations;
+		
+		init_from_env();
 	}
 
 	void sg_global_print_default(FILE* target, const char* str)
@@ -170,4 +174,21 @@ namespace shogun
 		SG_REF(sg_rand);
 		return sg_rand;
 	}
+	
+	void init_from_env()
+	{
+		char* env_log_val = NULL;
+		SGIO* io = get_global_io();
+		env_log_val = getenv("SHOGUN_LOG_LEVEL");
+		if (env_log_val)
+		{
+			if(strncmp(env_log_val, "DEBUG", 5) == 0)
+				io->set_loglevel(MSG_DEBUG);
+			else if(strncmp(env_log_val, "WARN", 4) == 0)
+				io->set_loglevel(MSG_WARN);
+			else if(strncmp(env_log_val, "ERROR", 5) == 0)
+				io->set_loglevel(MSG_ERROR);
+		}
+		SG_UNREF(io);
+	}
 }
diff --git a/src/shogun/base/init.h b/src/shogun/base/init.h
index 2056ab3ee13..3e1a0f3bd29 100644
--- a/src/shogun/base/init.h
+++ b/src/shogun/base/init.h
@@ -106,6 +106,10 @@ void set_global_rand(CRandom* rand);
  */
 CRandom* get_global_rand();
 
+/** Checks environment variables and modifies global objects
+ */
+void init_from_env();
+
 /// function called to print normal messages
 extern void (*sg_print_message)(FILE* target, const char* str);
 
diff --git a/src/shogun/machine/gp/GaussianLikelihood.cpp b/src/shogun/machine/gp/GaussianLikelihood.cpp
index d364f61dbd2..42d451b8422 100644
--- a/src/shogun/machine/gp/GaussianLikelihood.cpp
+++ b/src/shogun/machine/gp/GaussianLikelihood.cpp
@@ -91,8 +91,8 @@ SGVector<float64_t> CGaussianLikelihood::get_log_probability_f(const CLabels* la
 
 	// compute log probability: lp=-(y-f).^2./sigma^2/2-log(2*pi*sigma^2)/2
 	eigen_result=eigen_y-eigen_f;
-	eigen_result=-eigen_result.cwiseProduct(eigen_result)/(2*CMath::sq(m_sigma))-
-		VectorXd::Ones(result.vlen)*log(2*CMath::PI*CMath::sq(m_sigma))/2.0;
+	eigen_result=-eigen_result.cwiseProduct(eigen_result)/(2.0*CMath::sq(m_sigma))-
+		VectorXd::Ones(result.vlen)*log(2.0*CMath::PI*CMath::sq(m_sigma))/2.0;
 
 	return result;
 }
@@ -150,7 +150,8 @@ SGVector<float64_t> CGaussianLikelihood::get_first_derivative(const CLabels* lab
 	SGVector<float64_t> y=((CRegressionLabels*)lab)->get_labels();
 	Map<VectorXd> eigen_y(y.vector, y.vlen);
 
-	// compute derivative of log probability wrt sigma:
+	// compute derivative of log probability wrt log_sigma:
+	// dlp_dlogsigma
 	// lp_dsigma=(y-f).^2/sigma^2-1
 	eigen_result=eigen_y-eigen_f;
 	eigen_result=eigen_result.cwiseProduct(eigen_result)/CMath::sq(m_sigma);
@@ -179,9 +180,10 @@ SGVector<float64_t> CGaussianLikelihood::get_second_derivative(const CLabels* la
 	SGVector<float64_t> y=((CRegressionLabels*)lab)->get_labels();
 	Map<VectorXd> eigen_y(y.vector, y.vlen);
 
-	// compute derivative of the first derivative of log probability wrt sigma:
+	// compute derivative of (the first log_sigma derivative of log probability) wrt f:
+	// d2lp_dlogsigma_df == d2lp_df_dlogsigma
 	// dlp_dsigma=2*(f-y)/sigma^2
-	eigen_result=2*(eigen_f-eigen_y)/CMath::sq(m_sigma);
+	eigen_result=2.0*(eigen_f-eigen_y)/CMath::sq(m_sigma);
 
 	return result;
 }
@@ -203,9 +205,10 @@ SGVector<float64_t> CGaussianLikelihood::get_third_derivative(const CLabels* lab
 	SGVector<float64_t> result(func.vlen);
 	Map<VectorXd> eigen_result(result.vector, result.vlen);
 
-	// compute derivative of the second derivative of log probability wrt sigma:
-	// d2lp_dsigma=1/sigma^2
-	eigen_result=2*VectorXd::Ones(result.vlen)/CMath::sq(m_sigma);
+	// compute derivative of (the derivative of the first log_sigma derivative of log probability) wrt f:
+	// d3lp_dlogsigma_df_df == d3lp_df_df_dlogsigma
+	// d2lp_dsigma=2/sigma^2
+	eigen_result=2.0*VectorXd::Ones(result.vlen)/CMath::sq(m_sigma);
 
 	return result;
 }
diff --git a/src/shogun/machine/gp/GaussianLikelihood.h b/src/shogun/machine/gp/GaussianLikelihood.h
index a1b66dd92ae..c5970fde45e 100644
--- a/src/shogun/machine/gp/GaussianLikelihood.h
+++ b/src/shogun/machine/gp/GaussianLikelihood.h
@@ -216,7 +216,7 @@ class CGaussianLikelihood: public CLikelihoodModel
 	virtual float64_t get_first_moment(SGVector<float64_t> mu,
 			SGVector<float64_t> s2, const CLabels* lab, index_t i) const;
 
-	/** returns the second moment of a given (unnormalized) probability
+	/** returns the second central moment of a given (unnormalized) probability
 	 * distribution \f$q(f_i) = Z_i^-1
 	 * p(y_i|f_i)\mathcal{N}(f_i|\mu,\sigma^2)\f$, where \f$ Z_i=\int
 	 * p(y_i|f_i)\mathcal{N}(f_i|\mu,\sigma^2) df_i\f$.