added compiling (but not running) examples of kernel selection for MMD

examples/meta/src/statistical_testing/linear_time_mmd_kernel_selection.sg

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+GaussianBlobsDataGenerator features_p_train()
+GaussianBlobsDataGenerator features_q_train()
+GaussianBlobsDataGenerator features_p_test()
+GaussianBlobsDataGenerator features_q_test()
+
+#![create_instance]
+LinearTimeMMD mmd()
+mmd.set_p(features_p_train)
+mmd.set_q(features_q_train)
+mmd.set_num_samples_p(100)
+mmd.set_num_samples_q(100)
+mmd.set_num_blocks_per_burst(100)
+#![create_instance]
+
+#![add_kernels]
+GaussianKernel kernel1(10, 0.1)
+GaussianKernel kernel2(10, 1)
+GaussianKernel kernel3(10, 10)
+mmd.add_kernel(kernel1)
+mmd.add_kernel(kernel2)
+mmd.add_kernel(kernel3)
+#![add_kernels]
+
+#![select_kernel_single]
+mmd.select_kernel(enum EKernelSelectionMethod.MAXIMIZE_POWER)
+GaussianKernel learnt_kernel_single = GaussianKernel:obtain_from_generic(mmd.get_kernel())
+Real width = learnt_kernel_single.get_width()
+#![select_kernel_single]
+
+#![select_kernel_combined]
+mmd.select_kernel(enum EKernelSelectionMethod.MAXIMIZE_POWER)
+CombinedKernel learnt_kernel_combined = CombinedKernel:obtain_from_generic(mmd.get_kernel())
+RealVector weights = learnt_kernel_combined.get_subkernel_weights()
+#![select_kernel_combined]
+
+#![perform_test]
+mmd.set_p(features_p_test)
+mmd.set_q(features_q_test)
+mmd.set_num_samples_p(100)
+mmd.set_num_samples_q(100)
+Real statistic = mmd.compute_statistic()
+Real p_value = mmd.compute_p_value(statistic)
+#![perform_test]

examples/meta/src/statistical_testing/quadratic_time_mmd_kernel_selection.sg

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+CSVFile f_features_p_train("../../data/two_sample_test_gaussian.dat")
+CSVFile f_features_q_train("../../data/two_sample_test_laplace.dat")
+CSVFile f_features_p_test("../../data/two_sample_test_gaussian.dat")
+CSVFile f_features_q_test("../../data/two_sample_test_laplace.dat")
+
+#![create_features]
+RealFeatures features_p_train(f_features_p_train)
+RealFeatures features_q_train(f_features_q_train)
+RealFeatures features_p_test(f_features_p_test)
+RealFeatures features_q_test(f_features_q_test)
+#![create_features]
+
+#![create_instance]
+QuadraticTimeMMD mmd(features_p_train, features_q_train)
+#![create_instance]
+
+#![add_kernels]
+GaussianKernel kernel1(10, 0.1)
+GaussianKernel kernel2(10, 1)
+GaussianKernel kernel3(10, 10)
+mmd.add_kernel(kernel1)
+mmd.add_kernel(kernel2)
+mmd.add_kernel(kernel3)
+#![add_kernels]
+
+#![select_kernel_single]
+mmd.select_kernel(enum EKernelSelectionMethod.MAXIMIZE_MMD)
+GaussianKernel learnt_kernel_single = GaussianKernel:obtain_from_generic(mmd.get_kernel())
+Real width = learnt_kernel_single.get_width()
+#![select_kernel_single]
+
+#![select_kernel_combined]
+mmd.select_kernel(enum EKernelSelectionMethod.MAXIMIZE_MMD)
+CombinedKernel learnt_kernel_combined = CombinedKernel:obtain_from_generic(mmd.get_kernel())
+RealVector weights = learnt_kernel_combined.get_subkernel_weights()
+#![select_kernel_combined]
+
+#![perform_test]
+mmd.set_p(features_p_test)
+mmd.set_q(features_q_test)
+Real statistic = mmd.compute_statistic()
+Real p_value = mmd.compute_p_value(statistic)
+#![perform_test]