R3 on "What are the most important statistical ideas of the past 50 years? " Andrew Gelman, Aki Vehtari(12)

R3(References on References on References) on "What are the most important statistical ideas of the past 50 years? " Andrew Gelman, Aki Vehtari(12)

R3 on "What are the most important statistical ideas of the past 50 years? " Andrew Gelman, Aki Vehtari(0)
https://qiita.com/kaizen_nagoya/items/a8eac9afbf16d2188901

What are the most important statistical ideas of the past 50 years?
Andrew Gelman, Aki Vehtari
https://arxiv.org/abs/2012.00174

# References 
## 12
Besag, J. (1986). On the statistical analysis of dirty pictures (with discussion). Journal of the Royal Statistical Society B 48, 259–302.

https://www.semanticscholar.org/paper/On-the-Statistical-Analysis-of-Dirty-Pictures-Besag/47865b56fee61d9c9ff477f7c79f090cc6663d3a#references

### References on 12
#### 12.1 
Classification of binary random patterns
K. Abend, T. Harley, L. Kanal
Mathematics, Computer Science
IEEE Trans. Inf. Theory 1965
TLDR
 A novel extension of Markov chain methods into two dimensions leads to the Markov mesh which economically takes care of a much larger class of spatial dependencies. Expand
281

#### 12.2
Research Feed
Bayes Smoothing Algorithms for Segmentation of Binary Images Modeled by Markov Random Fields
H. Derin, H. Elliott, R. Cristi, D. Geman
Mathematics, Medicine
IEEE Transactions on Pattern Analysis and Machine Intelligence
1984
TLDR
 The Bayes smoothing algorithm presented here is valid for scene random fields consisting of multilevel (discrete) or continuous random variables, and it gives the optimum Bayes estimate for the scene value at each pixel. Expand
210
Highly Influential


#### 12.3

Research Feed
Markov Random Field Texture Models
G. R. Cross, Anil K. Jain
Computer Science, Mathematics
IEEE Transactions on Pattern Analysis and Machine Intelligence
1983
TLDR
 The power of the binomial model to produce blurry, sharp, line-like, and blob-like textures is demonstrated and the synthetic microtextures closely resembled their real counterparts, while the regular and inhomogeneous textures did not. Expand
1,487
PDF


#### 12.4

Research Feed
Recursive contextual classification using a spatial stochastic model
T. Yu, K. Fu
Computer Science
Pattern Recognit.
1983
TLDR
 Detailed experimental results with remotely sensed multispectral scanner data using the developed model for contextual classification are reported, and classification results do show the effectiveness and efficiency of the developed contextual classifier. Expand
36


#### 12.5

Research Feed
Image restoration by a powerful maximum entropy method
S. Burch, S. Gull, J. Skilling
Mathematics, Computer Science
Comput. Vis. Graph. Image Process.
1983
TLDR
 The maximum entropy algorithm revealed detail on the images not seen in the linear restorations, but which are known to exist, in the reconstruction of images from sparse data, which no comparable linear algorithm can handle. Expand
155

#### 12.6

Research Feed
Comments on "Application of the Conditional Population-Mixture Model to Image Segmentation"
D. Titterington
Mathematics, Computer Science
IEEE Trans. Pattern Anal. Mach. Intell.
1984
TLDR
 It is pointed out that biases are incurred in parameter estimation, that the class memberships and parameters are conceptually different, and therefore that the so-called standard mixture likelihood is to be preferred. Expand
35


#### 12.7

Research Feed
Bayesian Image Analysis
D. Geman, S. Geman
Computer Science
1986
TLDR
 The use of MRFs and related stochastic processes as models for intensity data has been prevalent in the image processing literature for some time now and here the approach to image modelling and analysis along some different lines is pursued. Expand
35

#### 12.8

Research Feed
Statistical Analysis of Non‐Lattice Data
J. Besag
Mathematics
1975
In rather formal terms, the situation with which this paper is concerned may be described as follows. We are given a fixed system of n sites, labelled by the first n positive integers, and an… Expand
1,597
PDF


#### 12.9

Research Feed
PROBABILISTIC LABELING IN A HIDDEN SECOND ORDER MARKOV MESH
P. Devijver,  Mathematics, 1986
Abstract: In this paper, we address the pixel labeling problem under the assumption that contextual information in the picture is encoded in the transition probabilities of a second order Markov mesh… Expand
42
Highly Influential


#### 12.10

Research Feed
Scene Labeling by Relaxation Operations
A. Rosenfeld, R. Hummel, S. Zucker, Computer Science, IEEE Transactions on Systems, Man, and Cybernetics, 1976
 This paper formulates the ambiguity-reduction process in terms of iterated parallel operations (i.e., relaxation operations) performed on an array of object, identification data. Expand
1,554

#### 12.11

Image processing in a general purpose microcomputer
J. Russ, J. Russ
Computer Science
1984
TLDR
 Video images from light and electron microscopes can be acquired in ‘digital’ form within a personal computer, using standard peripherals and interfaces and combined with previous ones stored on disk is especially useful for electron and X‐ray images from SEM. Expand
23

#### 12.12

Research Feed
Monte Carlo Sampling Methods Using Markov Chains and Their Applications
W. K. Hastings
Mathematics
1970
SUMMARY A generalization of the sampling method introduced by Metropolis et al. (1953) is presented along with an exposition of the relevant theory, techniques of application and methods and… Expand
12,935
PDF


#### 12.13


Research Feed
Markov mesh models
L. Kanal
Computer Science
1980
52


#### 12.14
Research Feed
A neighbourhood-based classifier for LANDSAT data
A. Owen
Mathematics
1984
A classifier is developed which uses information from all pixels in a neighbourhood to classify the pixel at the center of the neighbourhood. It is not a smoother in that it tries to recognize… Expand
57

#### 12.15
Research Feed
On the Foundations of Relaxation Labeling Processes
R. Hummel, S. Zucker
Mathematics, Medicine
IEEE Transactions on Pattern Analysis and Machine Intelligence
1983
TLDR
 It is shown that the problem of finding consistent labelings is equivalent to solving a variational inequality, and a procedure nearly identical to the relaxation operator derived under restricted circum-stances serves in the more general setting. Expand
1,005

#### 12.16

Research Feed
Image reconstruction from incomplete and noisy data
S. Gull, G. Daniell
Physics
Nature
1978
Results are presented of a powerful technique for image reconstruction by a maximum entropy method, which is sufficiently fast to be useful for large and complicated images. Although our examples are… Expand
899
#### 12.17

Research Feed
Maximum Likelihood Reconstruction for Emission Tomography
L. Shepp, Y. Vardi
Mathematics
1982
Previous models for emission tomography (ET) do not distinguish the physics of ET from that of transmission tomography. We give a more accurate general mathematical model for ET where an unknown… Expand
3,558
#### 12.18

Research Feed
Maximum likelihood discriminant analysis on the plane using a Markovian model of spatial context
J. Haslett
Mathematics, Computer Science
Pattern Recognit.
1985
TLDR
 A method for utilising spatial information in performing discriminant analysis on multivariate data at each point on a regular lattice, as for example with LANDSAT, seems to be encouraging. Expand
103

#### 12.19

Research Feed
Metric Pattern Theory
U. Grenander
Computer Science
1981
TLDR
 Important advances have been made in metric pattern theory after the appearance of Volume I, some of which are contained in two reports by Hwang and Thrift; much of this chapter is devoted to presenting their results. Expand
9
#### 12.20

Research Feed
Image segmentation using simple Markov field models
F. Hansen, H. Elliott
Computer Science, Mathematics
Comput. Graph. Image Process.
1982
TLDR
 By modelling a picture as a two-state Markov field, MAP estimation techniques are used to develop suboptimal but computationally tractable binary segmentation algorithms that perform well at low signal-to-noise ratios. Expand
74

#### 12.21


Continuous Relaxation and Local Maxima Selection: Conditions for Equivalence
S. Zucker, Y. G. Leclerc, John L. Mohammed
Mathematics, Computer Science
IEEE Transactions on Pattern Analysis and Machine Intelligence
1981
TLDR
 A new perspective toward relaxation is introduced-that of considering it as a process for reordering labels attached to nodes in a graph, to establish the formal equivalence between relaxation and another widely used algorithm, local maxima selection. Expand
67

#### 12.22
Research Feed
Digital Picture Processing, Volume 1
A. Rosenfeld, A. Kak
Computer Science
1982
The rapid rate at which the field of digital picture processing has grown in the past five years had necessitated extensive revisions and the introduction of topics not found in the original edition.… Expand
302

#### 12.23
Research Feed
A Statistical Model for Positron Emission Tomography
Y. Vardi, L. Shepp, L. Kaufman
Mathematics, Physics
1985
Abstract Positron emission tomography (PET)—still in its research stages—is a technique that promises to open new medical frontiers by enabling physicians to study the metabolic activity of the body… Expand
848
PDF

#### 12.24
Research Feed
Maximal Flow Through a Network
L. R. Ford, D. R. Fulkerson
Mathematics
1956
Introduction. The problem discussed in this paper was formulated by T. Harris as follows: "Consider a rail network connecting two cities by way of a number of intermediate cities, where each link of… Expand
2,675


#### 12.25
Research Feed
Analysis of Field Experiments by Least Squares Smoothing
Peter Green, C. Jennison, A. Seheult
Mathematics
1985
SUMMARY Assuming a smooth trend plus independent error model for the environmental effects in the yields of a field plot experiment, least squares smoothing methods are developed to estimate both the… Expand
207

#### 12.26
Research Feed
On Spatial-Temporal Models and Markov Fields
J. Besag
Mathematics
1977
A short account of the Hammersley-Clifford theorem in the theory of Markov random fields is given. A class of time-reversible spatial-temporal processes is defined and is shown to generate the class… Expand
21


#### 12.27

Research Feed
Common structure of smoothing techniques in statistics
D. Titterington
Mathematics
1985
Summary A wide variety of statistical techniques involve the choice of a prescription and smoothing parameter for modifying an unsmoothed estimator towards some ultrasmooth solution. The basic common… Expand
220


#### 12.28
Research Feed
Some Aspects of the Spline Smoothing Approach to Non‐Parametric Regression Curve Fitting
B. Silverman
Mathematics
1985
Non-parametric regression using cubic splines is an attractive, flexible and widely-applicable approach to curve estimation. Although the basic idea was formulated many years ago, the method is not… Expand
981
PDF

#### 12.29
Research Feed
Unilateral Markov fields
D. Pickard
Mathematics
1980
Recently, there has been considerable interest in some specialized binary lattice processes. However, this exciting work has been rather fragmentary and heuristic. Rigorous proofs are provided for… Expand
113


#### 12.30
Research Feed
The comparison by simulation of solutions of Wicksell's corpuscle problem
R. Bloedner, P. Muehlig, W. Nagel
Mathematics
1984
In this paper six distribution‐free (nonparametric) stereological methods for the solution of Wicksell's corpuscle problem—i.e. the determination of the distribution of diameters of spheres embedded… Expand
19

#### 12.31
Clustering on coloured lattices
D. J. Strauss
Mathematics
1977
This paper is concerned with nearest-neighbour systems on the coloured lattice (unordered state space). It extends the paper of Strauss (1975) on clustering in the two-colour case. Comparison is made… Expand
59

#### 12.32
Research Feed
A three parameter isotropic distribution of atoms and the hard‐core square lattice gas
A. Verhagen
Physics
1977
A five parameter symmetric distribution of atom patterns on the unit cell of the square lattice is statistically continued to construct a five parameter distribution of atom patterns on the 2×∞… Expand
19
#### 12.33
Research Feed
Diffusions for global optimizations
S. Geman, C. Hwang
Mathematics
1986
We seek a global minimum of $U:[0,1]^n \to R$. The solution to $({d / {dt}})x_t = - \nabla U(x_t )$ will find local minima. The solution to $dx_t = - \nabla U(x_t )dt + \sqrt {2T} dw_t $, where w is… Expand
291
PDF
#### 12.34
Research Feed
Contextual Pattern Recognition Applied to Cloud Detection and Identification
J. Kittler, D. Pairman
Computer Science
IEEE Transactions on Geoscience and Remote Sensing
1985
TLDR
 A general contextual classification rule is developed which is then simplified under some realistic assumptions made and confirms its superiority over the conventional Bayes rule and provides justification for the assumption made. Expand
67
#### 12.35
Research Feed
Fading Characteristics of Panchromatic Radar Backscatter from Selected Agricultural Targets
T. Bush, Fawwaz Uloby
Environmental Science, Geology
IEEE Transactions on Geoscience Electronics
1975
An experiment was performed to determine the fading characteristics of backscattered radar signals from four agricultural targets at 9 GHz. The targets included two different row crops (corn and… Expand
45

#### 12.36
ON A TWO-DIMENSIONAL BINARY PROCESS
R. Galbraith, D. Walley
Mathematics
1976
We consider a two-dimensional stochastic process of binary variables xj defined so that the conditional distribution of x, given its predecessors depends only on x,_,, and x,,_,. Properties of the… Expand
18
Highly Influential

#### 12.37
Graphical and recursive models for contingency tables
N. Wermuth, S. Lauritzen
Mathematics
1983
SUMMARY We discuss two classes of models for contingency tables, graphical and recursive models, both of which arise from restrictions that are expressible as conditional independencies of variable… Expand
255

#### 12.38
Contextual classification of multispectral pixel data
J. Kittler, J. Föglein
Computer Science
Image Vis. Comput.
1984
Abstract Contextual statistical decision rules for classification of lattice-structured data such as pixels in multispectral imagery are developed. Their recursive implementation is shown to have a… Expand
110
#### 12.39
Optimization by Simulated Annealing
S. Kirkpatrick, C. D. Gelatt, M. Vecchi
Medicine, Computer Science
Science
1983
TLDR
 A detailed analogy with annealing in solids provides a framework for optimization of the properties of very large and complex systems. Expand
38,444
PDF

#### 12.40
Adaptive Relaxation Labeling
H. Kalayeh, D. Landgrebe
Mathematics, Medicine
IEEE Transactions on Pattern Analysis and Machine Intelligence
1984
TLDR
 It is shown that by having nonstationary compatibility coefficients (NSCC's) the PRL stabilizes about the minimum error which is obtained during the early iterations. Expand
14

#### 12.41
Extensions of linear discriminant analysis for statistical classification of remotely sensed satellite imagery
P. Switzer
Computer Science
1980
TLDR
 Extensions of this basic tool promise substantial improvements and this work examines the added effectiveness of the integration of spatial autocorrelation into the discriminant model, the resolution of nonhomogeneous pixels, and data based prior probability estimates of class membership. Expand
99

#### 12.42
On the covariance of two noncentral F random variables and the variance of the estimated liner discriminant function
F. Critchley, I. Ford
Mathematics
1984
SUMMARY The covariance of two noncentral F random variables with a common covariance matrix is obtained from which the variance of their difference follows easily. An application of this latter… Expand
9
#### 12.43
Confidence and Conflict in Multivariate Calibration
P. Brown, R. Sundberg
Mathematics
1987
SUMMARY Multivariate calibration involves using an estimated relationship between a multivariate response Y and an explanatory vector X to predict unknown X in future from further observed responses.… Expand
60
#### 12.44
Relaxation labelling and the entropy of neighbourhood information
J. Boyce, J. Feng, E. R. Haddow
Mathematics, Computer Science
Pattern Recognit. Lett.
1987
Abstract An entropy of neighbourhood information is defined for the nodes of a labelled graph. Its extrema coincide with the stationary points of a modified form of relaxation algorithm. The latter… Expand
9
#### 12.45
A Moment Inequality and Monotonicity of an Algorithm
B. Torsney
Mathematics
1983
Monotonicity of a proposed algorithm for a class of constrained optimisation problem is investigated. A moment lemma is proved which yields a condition sufficient for monotonicity. This condition is… Expand
59

#### 12.46
Probabilistic Reasoning in Predictive Expert Systems
D. Spiegelhalter
Computer Science
UAI
1985
TLDR
 Techniques in developing a coherent Probabilistic reasoning system are illustrated with reference to a simplified example and possible limitations of a formal probabilistic approach are discussed. Expand
153
#### 12.47
A Constraint-Propagation Approach to Probabilistic Reasoning
J. Pearl
Computer Science, Mathematics
UAI
1985
The paper demonstrates that strict adherence to probability theory does not preclude the use of concurrent, self-activated constraint-propagation mechanisms for managing uncertainty. Maintaining… Expand
215
PDF
#### 12.48
Discrimination and Classification
D. Hand
Engineering, Computer Science
1981
Presents different approaches to discrimination and classification problems from a statistical perspective. Provides computer projects concentrating on the most widely used and important algorithms,… Expand
1,182
#### 12.49
Positron emission tomography and autoradiography
J. Mazziotta, H. Schelbert
Medicine
1985
TLDR
 After reviewing the characteristics of cerebral and myocardial hemodynamics, transport, and metabolism, the contributors detail the theory of PET and autoradiography, the instrumentation required, and the procedures involved. Expand
167
#### 12.50
Gibbs States on Countable Sets
C. Preston
Mathematics
1974
1. Gibbs states and Markov random fields 2. Interacting particle systems 3. Coupled Markov chains 4. Gibbs states and Markov random fields on countable graphs 5. Gibbs states on countable sets 6.… Expand
320

#### 12.51
Global optimization via the Langevin equation
B. Gidas
Mathematics
1985 24th IEEE Conference on Decision and Control
1985
We provide a simple proof of the convergence of the cooling algorithms, i.e., the annealing algorithm and the Langevin equation. The convergence is established for temperature schedules which are… Expand
73
#### 12.52
A Model-Based Method for Computer-Aided Medical Decision-Making
S. Weiss, C. Kulikowski, S. Amarel, A. Safir
Computer Science
Artif. Intell.
1978
TLDR
 A general method of computer-assisted medical decision-making based on causal-associational network (CASNET) models of disease based on observations of a patient, pathophysiological states, and disease classifications for diagnosis and treatment of the glaucomas has been developed. Expand
498
PDF
#### 12.53
Minimum cuts and related problems
J. Picard, H. D. Ratliff
Mathematics, Computer Science
Networks
1975
TLDR
 This characterization of a cut in a network provides a fundamental equivalence between directed pseudosummetric networks and undirected networks and identifies a class of problems which can be solved as minimum cut problems on a network. Expand
236
#### 12.54
An algorithm for optimal designs on a design space
S. Silvey, D. Titterington, B. Torsney
Mathematics
1978
Two variations of a simple monotunic algorithm for computing optimal designs on a finite design space are presented. Various properties are listed. Comparisons witn other algorithms are made.
104
#### 12.55
Recursive causal models
H. Kiiveri, T. Speed, J. Carlin
Mathematics
1984
On introduit la notion de graphe causal recursif et on decrit les contraintes d'independance conditionnelle
201
PDF
#### 12.56
Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images
S. Geman, D. Geman
Computer Science, Mathematics
1984
6,424
Highly Influential
#### 12.57
Correlation properties of some nearest-neighbour models
Bull. Int. Statist. Inst.,
1969
A statistical view of uncertainty in expert systems
D. Spiegelhalter
Computer Science
1986
125
#### 12.58
Allocation of remotely sensed data using Markov models for spectral
1986
Image labelling and the statistical analysis of incomplete data
J. Kay, D. Titterington
Computer Science
1986
8
#### 12.59
Contextual classification of remotely sensed
1985
#### 12.60
A comparison of some contextual methods in remote sensing classification
1984
#### 12.61
Data analysis: The maximum entropy method
J. Skilling
Mathematics
Nature
1984
38

#### 12.61
Research Feed
The maximum entropy method for data analysis
D. Titterington
Mathematics
Nature
1984
26
#### 12.62
Some spatial statistics for the interpretation of satellite data (with Discussion)
Bull. Int. Statist. Inst.,
1983
#### 12.63
Maximum likelihood reconstruction in positron emission tomography
I.E.E.E. Trans. Medical Imaging,
1982
Maximum likelihood reconstruction in positron emission tomography
I.E.E.E. Trans. Medical Imaging
1982
#### 12.64
Pattern recognition : a statistical approach
P. Devijver, J. Kittler
Computer Science
1982
3,016
#### 12.65
Markov Random Fields and Their Applications
Ross Kindermann, J. Snell
Computer Science
1980
1,291
#### 12.66
Emission tomography.
H. Atkins
Medicine
New York state journal of medicine
1979
28
#### 12.67
An algorithm for optimal designs on a finite design space
Comnzun. in Statist., A
1978
#### 12.68

An algorithm for optimal designs on a finite design space
1978
#### 12.69
Relaxation processes for scene labelling: convergence, speed and stability
I. E. E.E. Trans. Systems, Man and Cybernetics
1978
#### 12.70
Relaxation processes for scene labelling: convergence, speed and stability
Systems, Man and Cybernetics,
1978
#### 12.71
A curious binary lattice process
D. Pickard
Mathematics
1977
75

#### 12.72
Efficiency of pseudolikelihood estimation for simple Gaussian fields
J. Besag
Mathematics
1977
370
#### 12.73
In discussion of Dempster, Laird and Rubin's paper
J. R. Statist. Soc. B
1977
#### 12.74
ClassiJication, Estimation and Pattern Recognition
ClassiJication, Estimation and Pattern Recognition
1974
ClassiJication, Estimation and Pattern Recognition
1974
Classification, Estimation and Pattern Recognition
T. Young, T. Calvert
Computer Science
1974
265


#### 12.75
SHOWING 81-83 OF 83 REFERENCES
SORT BY

Spatial Interaction and the Statistical Analysis of Lattice Systems
J. Besag
Mathematics
1974
5,963

#### 12.76
A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
L. Baum, T. Petrie, George W. Soules, Norman Weiss
Mathematics
1970
4,497
of the Paper by Professor Besag
#### 12.77
Statistical analysis of dirty pictures
J. Besag
Mathematics
1993
A continuous two-dimensional region is partitioned into a fine rectangular array of sites, or ‘pixels', each pixel havin...
75
#### 12.78
Image restoration via N-nearest neighbour classification
H. Cohen
Mathematics, Computer Science
Proceedings of 3rd IEEE International Conference…
1996
A novel and powerful perspective on image reconstruction and restoration is to regard the computational objective as the...
10
#### 12.79
Adaptive Bayesian Classification of Spatial Data
R. Klein, S. J. Press
Mathematics
1992
Abstract A two-dimensional scene is analyzed statistically by superimposing on it a rectangular grid and studying each s...
15

### 最後までおよみいただきありがとうございました。
いいね　💚、フォローをお願いします。
####  Thank you very much for reading to the last sentence.
Please press the like icon 💚　and follow me for your happy life.