@@ -162,9 +162,8 @@ public static <T> T[] sample(T[] source, double p) {
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* given source array. All n choose k combinations are equally
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* likely, where n is the length of the source array.</p>
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*
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- * <p>This method chooses among the samplePool,
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- * sampleReservoir, and sampleInsertion
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- * methods based on the values of n and k.</p>
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+ * <p>This method chooses among the {@link SequencePoolSampler}, {@link SequenceReservoirSampler},
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+ * and {@link SequenceInsertionSampler} classes based on the values of n and k.</p>
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*
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* <p>This approach combining reservoir sampling, pool sampling, and insertion sampling
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* was described in: Vincent A. Cicirello. 2022. <a href="https://www.cicirello.org/publications/applsci-12-05506.pdf">Cycle
@@ -195,9 +194,8 @@ public static int[] sample(int[] source, int k, int[] target) {
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* given source array. All n choose k combinations are equally
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* likely, where n is the length of the source array.</p>
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*
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- * <p>This method chooses among the samplePool,
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- * sampleReservoir, and sampleInsertion
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- * methods based on the values of n and k.</p>
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+ * <p>This method chooses among the {@link SequencePoolSampler}, {@link SequenceReservoirSampler},
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+ * and {@link SequenceInsertionSampler} classes based on the values of n and k.</p>
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*
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* <p>This approach combining reservoir sampling, pool sampling, and insertion sampling
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* was described in: Vincent A. Cicirello. 2022. <a href="https://www.cicirello.org/publications/applsci-12-05506.pdf">Cycle
@@ -228,9 +226,8 @@ public static long[] sample(long[] source, int k, long[] target) {
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* given source array. All n choose k combinations are equally
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* likely, where n is the length of the source array.</p>
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*
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- * <p>This method chooses among the samplePool,
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- * sampleReservoir, and sampleInsertion
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- * methods based on the values of n and k.</p>
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+ * <p>This method chooses among the {@link SequencePoolSampler}, {@link SequenceReservoirSampler},
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+ * and {@link SequenceInsertionSampler} classes based on the values of n and k.</p>
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*
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* <p>This approach combining reservoir sampling, pool sampling, and insertion sampling
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* was described in: Vincent A. Cicirello. 2022. <a href="https://www.cicirello.org/publications/applsci-12-05506.pdf">Cycle
@@ -261,9 +258,8 @@ public static short[] sample(short[] source, int k, short[] target) {
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* given source array. All n choose k combinations are equally
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* likely, where n is the length of the source array.</p>
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*
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- * <p>This method chooses among the samplePool,
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- * sampleReservoir, and sampleInsertion
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- * methods based on the values of n and k.</p>
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+ * <p>This method chooses among the {@link SequencePoolSampler}, {@link SequenceReservoirSampler},
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+ * and {@link SequenceInsertionSampler} classes based on the values of n and k.</p>
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*
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* <p>This approach combining reservoir sampling, pool sampling, and insertion sampling
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* was described in: Vincent A. Cicirello. 2022. <a href="https://www.cicirello.org/publications/applsci-12-05506.pdf">Cycle
@@ -294,9 +290,8 @@ public static byte[] sample(byte[] source, int k, byte[] target) {
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* given source array. All n choose k combinations are equally
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* likely, where n is the length of the source array.</p>
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*
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- * <p>This method chooses among the samplePool,
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- * sampleReservoir, and sampleInsertion
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- * methods based on the values of n and k.</p>
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+ * <p>This method chooses among the {@link SequencePoolSampler}, {@link SequenceReservoirSampler},
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+ * and {@link SequenceInsertionSampler} classes based on the values of n and k.</p>
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*
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* <p>This approach combining reservoir sampling, pool sampling, and insertion sampling
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* was described in: Vincent A. Cicirello. 2022. <a href="https://www.cicirello.org/publications/applsci-12-05506.pdf">Cycle
@@ -327,9 +322,8 @@ public static char[] sample(char[] source, int k, char[] target) {
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* given source String. All n choose k combinations are equally
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* likely, where n is the length of the source String.</p>
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*
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- * <p>This method chooses among the samplePool,
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- * sampleReservoir, and sampleInsertion
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- * methods based on the values of n and k.</p>
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+ * <p>This method chooses among the {@link SequencePoolSampler}, {@link SequenceReservoirSampler},
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+ * and {@link SequenceInsertionSampler} classes based on the values of n and k.</p>
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*
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* <p>This approach combining reservoir sampling, pool sampling, and insertion sampling
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* was described in: Vincent A. Cicirello. 2022. <a href="https://www.cicirello.org/publications/applsci-12-05506.pdf">Cycle
@@ -360,9 +354,8 @@ public static char[] sample(String source, int k, char[] target) {
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* given source array. All n choose k combinations are equally
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* likely, where n is the length of the source array.</p>
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*
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- * <p>This method chooses among the samplePool,
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- * sampleReservoir, and sampleInsertion
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- * methods based on the values of n and k.</p>
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+ * <p>This method chooses among the {@link SequencePoolSampler}, {@link SequenceReservoirSampler},
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+ * and {@link SequenceInsertionSampler} classes based on the values of n and k.</p>
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*
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* <p>This approach combining reservoir sampling, pool sampling, and insertion sampling
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* was described in: Vincent A. Cicirello. 2022. <a href="https://www.cicirello.org/publications/applsci-12-05506.pdf">Cycle
@@ -393,9 +386,8 @@ public static double[] sample(double[] source, int k, double[] target) {
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* given source array. All n choose k combinations are equally
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* likely, where n is the length of the source array.</p>
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*
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- * <p>This method chooses among the samplePool,
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- * sampleReservoir, and sampleInsertion
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- * methods based on the values of n and k.</p>
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+ * <p>This method chooses among the {@link SequencePoolSampler}, {@link SequenceReservoirSampler},
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+ * and {@link SequenceInsertionSampler} classes based on the values of n and k.</p>
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*
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* <p>This approach combining reservoir sampling, pool sampling, and insertion sampling
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* was described in: Vincent A. Cicirello. 2022. <a href="https://www.cicirello.org/publications/applsci-12-05506.pdf">Cycle
@@ -426,9 +418,8 @@ public static float[] sample(float[] source, int k, float[] target) {
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* given source array. All n choose k combinations are equally
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* likely, where n is the length of the source array.</p>
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*
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- * <p>This method chooses among the samplePool,
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- * sampleReservoir, and sampleInsertion
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- * methods based on the values of n and k.</p>
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+ * <p>This method chooses among the {@link SequencePoolSampler}, {@link SequenceReservoirSampler},
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+ * and {@link SequenceInsertionSampler} classes based on the values of n and k.</p>
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*
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* <p>This approach combining reservoir sampling, pool sampling, and insertion sampling
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* was described in: Vincent A. Cicirello. 2022. <a href="https://www.cicirello.org/publications/applsci-12-05506.pdf">Cycle
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