MANISERA, Marica
 Distribuzione geografica
Continente #
NA - Nord America 4.933
EU - Europa 4.375
AS - Asia 3.290
SA - Sud America 752
AF - Africa 106
OC - Oceania 19
Continente sconosciuto - Info sul continente non disponibili 18
Totale 13.493
Nazione #
US - Stati Uniti d'America 4.786
IT - Italia 2.316
CN - Cina 1.111
SG - Singapore 1.091
BR - Brasile 595
UA - Ucraina 575
HK - Hong Kong 368
DE - Germania 286
FR - Francia 214
VN - Vietnam 210
FI - Finlandia 171
GB - Regno Unito 159
PL - Polonia 125
TR - Turchia 119
RU - Federazione Russa 107
IE - Irlanda 102
NL - Olanda 90
CA - Canada 85
IN - India 83
BD - Bangladesh 77
EE - Estonia 71
AR - Argentina 66
ES - Italia 60
MX - Messico 32
PK - Pakistan 31
ZA - Sudafrica 31
JP - Giappone 30
ID - Indonesia 27
IQ - Iraq 26
NG - Nigeria 25
EC - Ecuador 24
BE - Belgio 18
MA - Marocco 18
SE - Svezia 18
EU - Europa 16
CO - Colombia 15
SA - Arabia Saudita 15
KR - Corea 14
TW - Taiwan 14
AU - Australia 12
PY - Paraguay 12
AT - Austria 11
CL - Cile 11
VE - Venezuela 11
AE - Emirati Arabi Uniti 9
PH - Filippine 9
CZ - Repubblica Ceca 8
PE - Perù 8
EG - Egitto 7
GR - Grecia 7
NZ - Nuova Zelanda 7
CR - Costa Rica 6
HN - Honduras 6
JO - Giordania 6
MY - Malesia 6
UY - Uruguay 6
UZ - Uzbekistan 6
DZ - Algeria 5
IL - Israele 5
JM - Giamaica 5
KE - Kenya 5
PT - Portogallo 5
TN - Tunisia 5
AL - Albania 4
BO - Bolivia 4
CH - Svizzera 4
ET - Etiopia 4
HR - Croazia 4
HU - Ungheria 4
KZ - Kazakistan 4
NP - Nepal 4
BB - Barbados 3
KG - Kirghizistan 3
MO - Macao, regione amministrativa speciale della Cina 3
OM - Oman 3
PS - Palestinian Territory 3
RO - Romania 3
AZ - Azerbaigian 2
BA - Bosnia-Erzegovina 2
DO - Repubblica Dominicana 2
IR - Iran 2
LT - Lituania 2
LU - Lussemburgo 2
MU - Mauritius 2
SN - Senegal 2
SY - Repubblica araba siriana 2
TH - Thailandia 2
TT - Trinidad e Tobago 2
XK - ???statistics.table.value.countryCode.XK??? 2
AO - Angola 1
BG - Bulgaria 1
BS - Bahamas 1
DK - Danimarca 1
DM - Dominica 1
GE - Georgia 1
KW - Kuwait 1
LA - Repubblica Popolare Democratica del Laos 1
LB - Libano 1
LK - Sri Lanka 1
MD - Moldavia 1
Totale 13.484
Città #
Singapore 545
Jacksonville 406
Ann Arbor 351
Ashburn 342
Fairfield 337
Hong Kong 337
Woodbridge 331
Beijing 240
Milan 239
Houston 236
Rome 203
Princeton 186
The Dalles 176
San Jose 160
Chandler 155
Wilmington 153
Salerno 147
Brescia 138
Cambridge 125
Nanjing 124
Warsaw 118
Seattle 112
New York 109
Dublin 100
Helsinki 99
Dearborn 98
Lauterbourg 95
Bologna 89
Istanbul 88
Los Angeles 87
Ho Chi Minh City 70
Tallinn 69
Dallas 60
Nanchang 60
Des Moines 59
Buffalo 54
Moscow 53
Naples 50
São Paulo 48
Turin 45
Orem 44
Shenyang 43
Hanoi 41
Chicago 35
Florence 35
Tianjin 34
Hebei 33
San Francisco 33
Munich 31
San Diego 29
Tokyo 29
Padova 27
Redondo Beach 27
Santa Clara 26
Brooklyn 23
Changsha 23
Trento 22
Vicenza 22
Abuja 21
Council Bluffs 21
Palermo 21
Verona 21
Groningen 20
Chennai 19
Jiaxing 19
Shanghai 19
Zhengzhou 19
Bari 18
Jinan 18
Afragola 17
Atlanta 17
Aversa 17
Belo Horizonte 17
Frankfurt am Main 17
Hangzhou 17
Johannesburg 17
Kunming 17
Venice 17
Genoa 16
London 16
Montreal 16
Amsterdam 15
Denver 15
Brussels 14
Manchester 14
Rio de Janeiro 14
Perugia 13
Poplar 13
Reggio Emilia 13
Toronto 13
Haiphong 12
Hefei 12
Trieste 12
Ancona 11
Bolzano 11
Casorezzo 11
Catania 11
Guayaquil 11
Lonigo 11
Ningbo 11
Totale 7.705
Nome #
Basketball Data Science: Basketball Analytics a portata di mano 882
Un’analisi delle relazioni tra equità, motivazione e soddisfazione per il lavoro 366
"P" come Piacere 289
Nell’era dei Big Data gli statistici contano… anche nello sport 219
Modelling the dynamic pattern of surface area in basketball and its effects on team performance 209
Big data analytics to model scoring probability in basketball: the effect of shooting under high-pressure conditions 196
Assessing Stability in NonLinear PCA with Hierarchical Data 174
Clustering ranking data in market segmentation: a case study on the Italian McDonald's customers’ preferences 168
Statistics in Sports 168
Basketball spatial performance indicators 166
Guest Editorial ‘Statistical Modelling for Sports Analytics’ 163
Alley‐oop! Basketball analytics in R 163
On Pinto da Costa & Soares’ and other Weighted Rank Correlation Measures deriving from the Spearman’s rho 161
Sensory analysis in the food industry as a tool for marketing decisions 159
Modeling “don't know” responses in rating scales 157
A graphical tool to compare groups of subjects on categorical variables 155
Assessing Stability in Nonlinear PCA with Hierarchical Data 154
Sensor Analytics in Basketball 150
On the nonlinearity of homogeneous ordinal variables 147
Guest Editorial ‘Statistical Modelling for Sports Analytics’ 147
On the nonlinearity of homogeneous ordinal variables 143
Space-Time Analysis of Movements in Basketball using Sensor Data 143
Estimation of Nonlinear CUB models via numerical optimization and EM algorithm 142
Analysing ordinal data to measure customer satisfaction: a comparison between the Rasch Model and CatPCA 141
Analyzing ordinal data to measure customer satisfaction: a comparison between the Rasch Model and CatPCA 141
Identifying the component structure of satisfaction scales by Nonlinear Principal Components Analysis 140
A statistical analysis on sensory data: the Italian espresso case study 140
Un’analisi esplorativa della qualità del lavoro nelle cooperative sociali 137
Evaluation of term-weighting measures for grouped text documents with a target variable: a simulation study 136
On the imputation of missing data in surveys with Likert-type scales 136
On the Imputation of Missing Data in Surveys with Likert-Type Scales 135
Identifiability of a model for discrete frequency distributions with a multidimensional parameter space 135
A SURVIVAL ANALYSIS STUDY TO DISCOVER WHICH SKILLS DETERMINE A HIGHER SCORING IN BASKETBALL 133
Modeling rating data with Nonlinear CUB models 133
Categorical Principal Component Analysis to identify the component structure of alexithymia 132
On two classes of Weighted Rank Correlation measures deriving from the Spearman’s rho 130
Assessing item contribution on unobservable variables’ measures with hierarchical data 129
Treatment of “don’t know” responses in the consumers’ perceptions about sustainability in the agri-food sector 128
Weighted Rank Correlation measures in Hierarchical Cluster Analysis 125
Interpreting clusters and their Bipolar Means: a case study 125
A graphical tool for comparing groups on categorical variables 122
BasketballAnalyzeR: an R package for basketball analytics 120
A nonlinear least squares solution of a minimax estimation problem for stationary time series 119
A Mixture Model for the Analysis of Categorical Variables Measured on Five-point Semantic Differential Scales 118
Discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence” by Domenico Piccolo and Rosaria Simone 117
Multilevel algorithmic models to measures item importance on latent variables’ indicators 116
A mixture model for rating data: the Nonlinear CUB 116
Basketball Data Science 116
The alexithymia construct: a reading based on Categorical Principal Component Analysis 115
Analyzing and modelling rating data for sensory analysis in food industry 115
Component structure of job satisfaction based on Herzberg's theory 114
Weighting the Spearman’s Rank Correlation Index 113
Visualizing Multiple Results from Nonlinear CUB Models with R Grid Viewports 113
Stime minimax per serie storiche stazionarie 111
Analisi dei criteri per la valutazione della ricerca individuale in ambito statistico, Relazione finale della Commissione SIS Riforma dei criteri condivisi per la valutazione della ricerca e revisione delle equivalenze dei titoli accademici europei ed internazionali da applicare alle “chiamate dirette”, available at http://sis-statistica.it/files/pdf/2010/relazione_finalecommissione_valutazione.pdf (retrieved April, 2011) 111
Treatment of 'don't know' responses in rating data: effects on the heterogeneity of the CUB distribution 111
Nonlinear CUB models: some stylized facts 110
Ordinal data models for no-opinion responses in attitude surveys 110
Basket: misurare la performance sotto pressione 110
Constructing indicators of unobservable variables from parallel measurements 109
Spatial Performance Indicators and Graphs in Basketball 109
Nonlinear CUB models: the R code 108
Analyzing Basketball Data with BasketballAnalyzeR 106
Models for categorical data: a comparison between the Rasch model and nonlinear principal component analysis. 105
Markov switching modelling of shooting performance variability and teammate interactions in basketball 105
Scoring ordinal variables for constructing composite indicators 104
Basketball analytics using spatial tracking data 104
Treatment of ‘don’t know’ responses in a mixture model for rating data 103
Minimax estimates for stationary time series 102
CUB models for sensory analysis in food industry 102
On some weighted rank correlation measures related to the Spearman’s rho 101
A mixture model for ordinal variables measured on semantic differential scales 101
Integration of model-based recursive partitioning with bias reduction estimation: a case study assessing the impact of Oliver’s four factors on the probability of winning a basketball game 99
Which achievements are associated with a better offensive performance in NBA? A survival analysis study 97
Robust estimation for stationary ARMA time series 96
Sulla scelta dello scaling level nell’Analisi delle Componenti Principali Nonlineare 95
Scoring ordinal variables for constructing composite indicators 94
Finding number of groups using a penalized internal cluster quality index 94
On the equivalence of two mixture models for rating data 93
Il profilo socio-demografico dei lavoratori 93
Group-specific document embeddings: an application to user-generated content 92
Scale Construction for Job Satisfaction by Categorical Principal Component Analysis 91
Advances in basketball statistics 91
L’Analisi delle Componenti Principali Nonlineare per la misurazione della qualità del lavoro 90
Modelling perceived variety in a choice process with nonlinear CUB 90
Minimax estimation based on a L1-metric loss function for stationary time series 88
Book of short papers, IES 2025 - Innovation & Society: Statistics and Data Science for Evaluation and Quality 87
New perspectives on rating data modelling: the Nonlinear CUB 86
Scoring probability maps in the basketball court with Indicator Kriging estimation 83
Exploring the quality of work in social cooperatives by a graphical tool 83
How perceived variety impacts on choice satisfaction: a two-step approach using the CUB class of models and best-subset variable selection 82
Motivazioni, atteggiamenti ed incentivi non economici del lavoro nelle cooperative sociali 81
Measuring job satisfaction by means of Nonlinear Principal Component Analysis 80
Sport Analytics: la statistica divertente 80
Measuring Nonlinearity in Data Analysis 79
Tecniche di scaling per la costruzione di indicatri della qualità del lavoro nel settore dei servizi sociali 75
Nonlinear CUB models 75
Il vino di qualità costa di più? Un’analisi per comprendere se e quanto la qualità del vino incida sul prezzo di mercato dei vini rossi italiani 73
A New Approach to Basketball Game Predictions by Simulating Games Based on the Predicted Numbers and Types of Plays 72
La statistica fa canestro 72
Totale 13.044
Categoria #
all - tutte 56.127
article - articoli 0
book - libri 0
conference - conferenze 0
curatela - curatele 0
other - altro 0
patent - brevetti 0
selected - selezionate 0
volume - volumi 0
Totale 56.127


Totale Lug Ago Sett Ott Nov Dic Gen Feb Mar Apr Mag Giu
2021/2022730 51 121 21 45 7 22 32 51 40 99 62 179
2022/2023703 106 14 29 48 61 150 11 45 128 29 39 43
2023/20241.182 79 30 114 120 52 112 74 90 238 62 41 170
2024/20252.423 65 41 51 372 207 200 215 105 319 133 458 257
2025/20264.059 349 541 331 682 479 188 512 177 269 278 166 87
2026/202786 86 0 0 0 0 0 0 0 0 0 0 0
Totale 13.736