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Outline Probability (Random) Sampling
, 2015
"... Simple random sampling (SRS) Systematic sampling Stratified sampling Cluster sampling Multistage sampling NonProbability Sampling Convenience sampling Volunteer sampling Judgment (Purposive) sampling Snowball sampling Quota sampling ..."
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Simple random sampling (SRS) Systematic sampling Stratified sampling Cluster sampling Multistage sampling NonProbability Sampling Convenience sampling Volunteer sampling Judgment (Purposive) sampling Snowball sampling Quota sampling
Simple Random Sampling
"... Abstract The present paper deals with a modification on the selection of linear systematic sample of odd size. Consequently the proposed method is called modified linear systematic sampling. The performances of the modified linear systematic sampling are assessed with that of simple random sampli ..."
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Abstract The present paper deals with a modification on the selection of linear systematic sample of odd size. Consequently the proposed method is called modified linear systematic sampling. The performances of the modified linear systematic sampling are assessed with that of simple random
CURE: An Efficient Clustering Algorithm for Large Data sets
 Published in the Proceedings of the ACM SIGMOD Conference
, 1998
"... Clustering, in data mining, is useful for discovering groups and identifying interesting distributions in the underlying data. Traditional clustering algorithms either favor clusters with spherical shapes and similar sizes, or are very fragile in the presence of outliers. We propose a new clustering ..."
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Cited by 722 (5 self)
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of random sampling and partitioning. A random sample drawn from the data set is first partitioned and each partition is partially clustered. The partial clusters are then clustered in a second pass to yield the desired clusters. Our experimental results confirm that the quality of clusters produced by CURE
Randomly Sampling Unlabelled Structures
, 1999
"... Informally, an \unlabelled combinatorial structure" is an object such as an unlabelled graph (in which the vertices are indistinguishable) or a structural isomer in chemistry (in which dierent atoms of the same type are indistinguishable). Computational experiments such as those described in ..."
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Cited by 2 (0 self)
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in this volume often rely on random sampling to generate inputs for the experiments. This paper surveys work on the problem of eciently sampling unlabelled combinatorial structures from a uniform distribution. 1 Introduction Most of the experimental work described in this volume involves rst randomly
On the Resemblance and Containment of Documents
 In Compression and Complexity of Sequences (SEQUENCES’97
, 1997
"... Given two documents A and B we define two mathematical notions: their resemblance r(A, B)andtheircontainment c(A, B) that seem to capture well the informal notions of "roughly the same" and "roughly contained." The basic idea is to reduce these issues to set intersection probl ..."
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Cited by 506 (6 self)
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problems that can be easily evaluated by a process of random sampling that can be done independently for each document. Furthermore, the resemblance can be evaluated using a fixed size sample for each document.
RANDOM SAMPLING OF BANDLIMITED FUNCTIONS
, 2008
"... We consider the problem of random sampling for bandlimited functions. When can a bandlimited function f be recovered from randomly chosen samples f(xj), j ∈ J ⊂ N? We estimate the probability that a sampling inequality of the form ..."
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Cited by 2 (1 self)
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We consider the problem of random sampling for bandlimited functions. When can a bandlimited function f be recovered from randomly chosen samples f(xj), j ∈ J ⊂ N? We estimate the probability that a sampling inequality of the form
Empirical exchange rate models of the Seventies: do they fit out of sample?
 JOURNAL OF INTERNATIONAL ECONOMICS
, 1983
"... This study compares the outofsample forecasting accuracy of various structural and time series exchange rate models. We find that a random walk model performs as well as any estimated model at one to twelve month horizons for the dollar/pound, dollar/mark, dollar/yen and tradeweighted dollar exch ..."
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Cited by 854 (12 self)
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This study compares the outofsample forecasting accuracy of various structural and time series exchange rate models. We find that a random walk model performs as well as any estimated model at one to twelve month horizons for the dollar/pound, dollar/mark, dollar/yen and tradeweighted dollar
Improving Coevolution by Random Sampling
"... Recent developments cast doubts on the effectiveness of coevolutionary learning in interactive domains. A simple evolution with fitness evaluation based on games with random strategies has been found to generalize better than competitive coevolution. In an attempt to investigate this phenomenon, ..."
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Cited by 6 (3 self)
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as evolution with random sampling for the expected utility performance measure. To investigate the differences between analyzed methods, we introduce performance profile, a tool that measures the player’s performance against opponents of various strength. The profiles reveal that evolution with random
Random sampling for subspace face recognition
 International Journal of Computer Vision
, 2006
"... Abstract. Subspace face recognition often suffers from two problems: (1) the training sample set is small compared with the high dimensional feature vector; (2) the performance is sensitive to the subspace dimension. Instead of pursuing a single optimal subspace, we develop an ensemble learning fram ..."
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Cited by 52 (18 self)
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framework based on random sampling on all three key components of a classification system: the feature space, training samples, and subspace parameters. Fisherface and Null Space LDA (NLDA) are two conventional approaches to address the small sample size problem. But in many cases, these LDA classifiers
On the Competitive Ratio of the Random Sampling Auction
 In Proc. 1st Workshop on Internet and Network Economics
, 2005
"... Abstract. We give a simple analysis of the competitive ratio of the random sampling auction from [10]. The random sampling auction was first shown to be worstcase competitive in [9] (with a bound of 7600 on its competitive ratio); our analysis improves the bound to 15. In support of the conjecture ..."
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Cited by 28 (8 self)
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Abstract. We give a simple analysis of the competitive ratio of the random sampling auction from [10]. The random sampling auction was first shown to be worstcase competitive in [9] (with a bound of 7600 on its competitive ratio); our analysis improves the bound to 15. In support of the conjecture
Results 11  20
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