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Portmanteau test

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275: 87:, having been devised at essentially the same time; a seemingly trivial simplification (omitted in the improved test) was found to have a deleterious effect. This portmanteau test is useful in working with 172: 316: 106:
has been devised, which allows a general test to be made for the possibility that a range of types nonlinear transformations of combinations of the
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Box, G. E. P.; Pierce, D. A. (1970). "Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models".
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is more loosely specified. Tests constructed in this context can have the property of being at least moderately
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match to a dataset where there are many different ways in which the model may depart from the underlying
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against a wide range of departures from the null hypothesis. Thus, in
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should have been included in addition to a selected model structure.
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in the residuals of a model: it tests whether any of a group of
290: 209:"A Low-Dimension Portmanteau Test for Non-linearity" 132:"On a measure of lack of fit in time series models" 173:Journal of the American Statistical Association 207:Castle, Jennifer L.; Hendry, David F. (2010). 310: 8: 250:. New York: John Wiley & Sons. pp.  79:are different from zero. This test is the 317: 303: 159:from the original on September 23, 2017. 119: 83:, which is an improved version of the 98:, including regression analysis with 7: 271: 269: 130:Ljung, G. M.; Box, G. E. P. (1978). 125: 123: 14: 273: 246:Applied Econometric Time Series 63:, two well-known versions of a 186:10.1080/01621459.1970.10481180 67:are available for testing for 1: 336:Time series statistical tests 230:10.1016/j.jeconom.2010.01.006 289:. You can help Knowledge by 31:is well specified, but the 25:statistical hypothesis test 367: 268: 16:Type of statistical test 217:Journal of Econometrics 153:10.1093/biomet/65.2.297 49:data generating process 341:Regression diagnostics 285:-related article is a 33:alternative hypothesis 108:explanatory variables 61:time series analysis 242:Enders, W. (1995). 96:regression analysis 180:(332): 1509–1526. 94:In the context of 41:applied statistics 298: 297: 358: 351:Statistics stubs 319: 312: 305: 277: 270: 265: 249: 234: 233: 213: 204: 198: 197: 167: 161: 160: 136: 127: 104:portmanteau test 75:of the residual 73:autocorrelations 65:portmanteau test 21:portmanteau test 366: 365: 361: 360: 359: 357: 356: 355: 346:Autocorrelation 326: 325: 324: 323: 262: 241: 238: 237: 211: 206: 205: 201: 169: 168: 164: 134: 129: 128: 121: 116: 85:Box–Pierce test 69:autocorrelation 57: 29:null hypothesis 17: 12: 11: 5: 364: 362: 354: 353: 348: 343: 338: 328: 327: 322: 321: 314: 307: 299: 296: 295: 278: 267: 266: 260: 236: 235: 224:(2): 231–245. 199: 162: 147:(2): 297–303. 118: 117: 115: 112: 102:structures, a 81:Ljung–Box test 56: 53: 15: 13: 10: 9: 6: 4: 3: 2: 363: 352: 349: 347: 344: 342: 339: 337: 334: 333: 331: 320: 315: 313: 308: 306: 301: 300: 294: 292: 288: 284: 279: 276: 272: 263: 257: 253: 248: 247: 240: 239: 231: 227: 223: 219: 218: 210: 203: 200: 195: 191: 187: 183: 179: 175: 174: 166: 163: 158: 154: 150: 146: 142: 141: 133: 126: 124: 120: 113: 111: 109: 105: 101: 97: 92: 90: 86: 82: 78: 74: 70: 66: 62: 54: 52: 50: 46: 42: 38: 34: 30: 27:in which the 26: 23:is a type of 22: 291:expanding it 280: 245: 221: 215: 202: 177: 171: 165: 144: 138: 103: 93: 64: 58: 20: 18: 100:time series 77:time series 330:Categories 283:statistics 261:0471039411 140:Biometrika 114:References 157:Archived 91:models. 55:Examples 37:powerful 194:2284333 45:model's 258:  192:  281:This 254:–87. 212:(PDF) 190:JSTOR 135:(PDF) 89:ARIMA 287:stub 256:ISBN 226:doi 222:158 182:doi 149:doi 59:In 332:: 252:86 220:. 214:. 188:. 178:65 176:. 155:. 145:65 143:. 137:. 122:^ 19:A 318:e 311:t 304:v 293:. 264:. 232:. 228:: 196:. 184:: 151::

Index

statistical hypothesis test
null hypothesis
alternative hypothesis
powerful
applied statistics
model's
data generating process
time series analysis
autocorrelation
autocorrelations
time series
Ljung–Box test
Box–Pierce test
ARIMA
regression analysis
time series
explanatory variables


"On a measure of lack of fit in time series models"
Biometrika
doi
10.1093/biomet/65.2.297
Archived
Journal of the American Statistical Association
doi
10.1080/01621459.1970.10481180
JSTOR
2284333
"A Low-Dimension Portmanteau Test for Non-linearity"

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