Modeling Various Survival Distributions using a Nonparametric Hypothesis Testing Based on Laplace Transform Approach with Some Real Applications

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr class="thead"><td class="align_left">Distribution</td><td class="align_center"><span style="width: 64.7766ptpx;"><svg height="12.5794pt" id="M87" style="vertical-align:-3.29107pt" version="1.1" viewbox="-0.0498162 -9.28833 64.7766 12.5794" width="64.7766pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M391 364C391 409 353 448 295 448C249 448 198 426 152 393C65 331 23 225 23 139C23 14 96 -12 146 -12C198 -12 280 9 367 101L351 124C300 78 242 48 194 48C129 48 109 107 109 162V191C208 213 391 266 391 364ZM313 350C313 305 268 261 113 223C132 334 187 381 217 398C227 404 244 405 261 405C290 405 313 385 313 350Z"></path></g><g transform="matrix(.013,0,0,-0.013,5.382,0)"><path d="M300 -147C201 -63 143 98 143 270S200 602 300 686L282 710C136 610 70 450 70 271V270C70 89 136 -72 282 -170L300 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transform="matrix(.0065,0,0,-0.0065,57.405,6.142)"><path d="M513 91L497 125C461 87 438 71 424 71C416 71 410 77 419 106C440 174 459 243 472 310C497 441 467 454 445 454C419 454 393 443 360 424C319 400 237 344 180 265H178L196 336C217 421 207 454 182 454C146 454 84 416 25 354L42 318C66 342 103 368 113 368C119 368 124 362 117 333L31 -2L41 -12C59 -3 91 5 119 11C133 76 146 123 162 180C214 262 337 384 383 384C404 384 411 371 391 304C370 233 350 165 333 90C318 24 328 -12 359 -12C385 -12 449 23 513 91Z"></path></g><g transform="matrix(.013,0,0,-0.013,64.394,0)"><path d="M275 270C275 450 212 609 64 710L45 686C145 604 203 442 203 270S147 -63 45 -147L64 -170C213 -68 275 89 275 270Z"></path></g></svg></span></td></tr><tr><td class="thead-hr" colspan="5"><hr/></td></tr><tr><td class="align_left">LFR</td><td class="align_center">5.76</td><td class="align_center">5.85</td><td class="align_center">15.2</td><td class="align_center">15.67</td></tr><tr><td class="align_left">Weibull</td><td class="align_center">0.93</td><td class="align_center">0.98</td><td class="align_center">43.20</td><td class="align_center">45.6</td></tr><tr><td class="align_left">Makeham</td><td class="align_center">5.69</td><td class="align_center">5.80</td><td class="align_center">10.2</td><td class="align_center">10.41</td></tr><tr class="table-tr"><td colspan="5"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Relative efficiency of <svg height="9.49473pt" id="M84" style="vertical-align:-0.2063999pt" version="1.1" viewbox="-0.0498162 -9.28833 6.84582 9.49473" width="6.84582pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M494 514C482 587 419 712 303 712C238 712 174 667 174 603C174 561 205 514 249 449C219 438 187 422 162 407C93 366 23 283 23 177C23 69 87 -12 190 -12C244 -12 288 5 328 33C406 87 444 170 444 249C444 329 404 391 331 475C265 550 222 605 222 627C222 647 238 657 267 657C355 657 421 585 484 499L494 514ZM359 234C359 143 319 30 219 30C172 30 114 75 114 178C114 275 163 343 195 378C212 397 241 415 269 425C305 382 359 313 359 234Z"></path></g></svg> with respect to <svg height="11.927pt" id="M85" style="vertical-align:-3.291101pt" version="1.1" viewbox="-0.0498162 -8.6359 13.9127 11.927" width="13.9127pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M715 650H476L470 622C550 619 562 610 562 570C562 536 553 481 535 384L523 321C485 121 408 37 283 37C178 37 99 109 134 297L178 532C193 612 199 616 278 622L284 650H29L23 622C105 616 109 609 94 532L48 291C23 160 51 83 98 40C143 -1 202 -16 260 -16C321 -16 387 3 439 49C509 111 542 204 563 312L577 384C595 479 608 533 619 569C629 603 637 620 709 622L715 650Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,8.606,3.132)"><path d="M504 89L488 119C453 85 428 69 416 69C408 69 405 75 412 102L462 304C492 438 460 451 436 451S388 441 356 423C311 397 229 336 170 256H168L189 340C208 418 200 451 177 451C144 451 82 413 24 352L40 322C65 345 98 369 108 369C114 369 119 363 112 335L28 -3L36 -12C54 -3 83 4 112 10C125 73 138 122 153 174C205 258 328 382 376 382C395 382 399 369 384 305L330 93C312 25 323 -12 351 -12C378 -12 439 21 504 89Z"></path></g></svg> and <span class="nowrap"><svg height="18.8166pt" id="M86" style="vertical-align:-6.250501pt" version="1.1" viewbox="-0.0498162 -12.5661 18.3322 18.8166" width="18.3322pt" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink"><g transform="matrix(.013,0,0,-0.013,0,0)"><path d="M494 514C482 587 419 712 303 712C238 712 174 667 174 603C174 561 205 514 249 449C219 438 187 422 162 407C93 366 23 283 23 177C23 69 87 -12 190 -12C244 -12 288 5 328 33C406 87 444 170 444 249C444 329 404 391 331 475C265 550 222 605 222 627C222 647 238 657 267 657C355 657 421 585 484 499L494 514ZM359 234C359 143 319 30 219 30C172 30 114 75 114 178C114 275 163 343 195 378C212 397 241 415 269 425C305 382 359 313 359 234Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,6.722,-6.049)"><path d="M309 -142C211 -61 151 99 151 271S210 601 309 683L288 710C141 611 75 451 75 272V271C75 90 141 -72 288 -169L309 -142Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,9.98,-6.049)"><path d="M414 144C384 79 371 75 317 75H135L276 221C367 316 408 376 408 465C408 570 327 635 237 635C179 635 131 609 100 575L42 494L67 471C94 510 138 565 205 565C277 565 321 517 321 435C321 348 258 270 195 195C146 137 88 81 33 26V0H411C423 44 433 88 446 135L414 144Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,14.412,-6.049)"><path d="M283 271C283 451 220 610 70 710L48 683C146 603 207 443 207 271S149 -59 48 -142L70 -169C220 -67 283 90 283 271Z"></path></g><g transform="matrix(.0091,0,0,-0.0091,6.396,4.041)"><path d="M606 650H137L129 618C217 609 221 609 203 518L129 129C115 46 106 40 26 32L18 0H300L307 32C210 40 203 45 218 129L249 305H358C454 305 455 296 457 219H491L531 425H497C465 353 463 350 366 350H259L300 569C306 605 310 611 346 611H444C522 611 535 598 541 578C550 557 553 519 552 485L588 489L606 650Z"></path></g><g transform="matrix(.0065,0,0,-0.0065,11.219,6.142)"><path d="M513 91L497 125C461 87 438 71 424 71C416 71 410 77 419 106C440 174 459 243 472 310C497 441 467 454 445 454C419 454 393 443 360 424C319 400 237 344 180 265H178L196 336C217 421 207 454 182 454C146 454 84 416 25 354L42 318C66 342 103 368 113 368C119 368 124 362 117 333L31 -2L41 -12C59 -3 91 5 119 11C133 76 146 123 162 180C214 262 337 384 383 384C404 384 411 371 391 304C370 233 350 165 333 90C318 24 328 -12 359 -12C385 -12 449 23 513 91Z"></path></g></svg>.</span></div>

Computational and Mathematical Methods in Medicine

tab3

Table 3

Table 3: Modeling Various Survival Distributions using a Nonparametric Hypothesis Testing Based on Laplace Transform Approach with Some Real Applications 

Table 3 | Modeling Various Survival Distributions using a Nonparametric Hypothesis Testing Based on Laplace Transform Approach with Some Real Applications 